{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exercises "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Applied"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.model_selection import GridSearchCV,train_test_split,cross_val_score\n",
    "from mlxtend.plotting import plot_decision_regions\n",
    "\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "import warnings \n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Generate a simulated two-class data set with 100 observations and two features in which there is a visible but non-linear separation between the two classes. Show that in this setting, a support vector machine with a polynomial kernel (with degree greater than 1) or a radial kernel will outperform a support vector classifier on the training data. Which technique performs best on the test data? Make plots and report training and test error rates in order to back up your assertions.\n",
    "\n",
    "\n",
    " \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(1)\n",
    "X = np.random.randn(100,2)\n",
    "data = pd.DataFrame(X,columns = ['X1','X2'])\n",
    "y = 1*(data['X1']**4 - data['X2'] > 1) #select classes such that there is a non linear relation\n",
    "data['y'] = y\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2049e833f98>"
      ]
     },
     "execution_count": 204,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,6))\n",
    "sns.scatterplot(x = 'X1',y = 'X2',hue = 'y',data = data,s = 50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Splitting the data into train and test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(50, 2) (50, 2)\n"
     ]
    }
   ],
   "source": [
    "X_train,X_test,y_train,y_test = train_test_split(data.drop('y',axis=1),data['y'],test_size = 0.5,random_state = 1)\n",
    "print(X_train.shape,X_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Support Vector Classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training score is  0.76\n",
      "Test score is  0.78\n"
     ]
    }
   ],
   "source": [
    "svc = SVC(kernel = 'linear')\n",
    "svc.fit(X_train,y_train)\n",
    "print('Training score is ',svc.score(X_train,y_train))\n",
    "print('Test score is ',svc.score(X_test,y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2049ef70278>"
      ]
     },
     "execution_count": 222,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,6))\n",
    "plot_decision_regions(np.array(data.drop('y',axis=1)), np.array(data['y']), clf=svc, legend=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Use SVM with non linear kernels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=5, error_score='raise-deprecating',\n",
       "             estimator=SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
       "                           decision_function_shape='ovr', degree=3,\n",
       "                           gamma='auto_deprecated', kernel='rbf', max_iter=-1,\n",
       "                           probability=False, random_state=None, shrinking=True,\n",
       "                           tol=0.001, verbose=False),\n",
       "             iid='warn', n_jobs=None, param_grid={'kernel': ['poly', 'rbf']},\n",
       "             pre_dispatch='2*n_jobs', refit=True, return_train_score=False,\n",
       "             scoring=None, verbose=0)"
      ]
     },
     "execution_count": 218,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#lets first of all choose which will be the better kernel among poly and rbf\n",
    "search = GridSearchCV(SVC(),param_grid={'kernel':['poly','rbf']},cv = 5)\n",
    "search.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'kernel': 'rbf'}"
      ]
     },
     "execution_count": 219,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "search.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training score -  1.0\n",
      "Test score -  0.92\n"
     ]
    }
   ],
   "source": [
    "best_model = search.best_estimator_\n",
    "print('training score - ',best_model.score(X_train,y_train))\n",
    "print('Test score - ',best_model.score(X_test,y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2049efe38d0>"
      ]
     },
     "execution_count": 223,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,6))\n",
    "\n",
    "plot_decision_regions(np.array(data.drop('y',axis=1)), np.array(data['y']), clf=best_model, legend=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "we are having test score of 0.92 using rbf as compared to 0.78 we had using svc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. We have seen that we can fit an SVM with a non-linear kernel in order to perform classification using a non-linear decision boundary. We will now see that we can also obtain a non-linear decision boundary by performing logistic regression using non-linear transformations of the features.\n",
    "\n",
    " \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (a) Generate a data set with n = 500 and p = 2, such that the observations belong to two classes with a quadratic decision boundary between them. For instance, you can do this as follows:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(8)\n",
    "X1 = np.random.uniform(0,1,500) - 0.5\n",
    "X2 = np.random.uniform(0,1,500) - 0.5\n",
    "\n",
    "y=1*(X1**2 - X2**2 > 0)\n",
    "\n",
    "data = pd.DataFrame({'X1':X1,'X2':X2,'y':y})\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (b) Plot the observations, colored according to their class labels.  Your plot should display X1 on the x-axis, and X2 on the yaxis.\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x27e71627978>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,6))\n",
    "sns.scatterplot(x = 'X1',y = 'X2',hue = 'y',data =data,s = 50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (c) Fit a logistic regression model to the data, using X1 and X2 as predictors.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train,X_test,y_train,y_test = train_test_split(data.drop('y',axis=1),data['y'],test_size = 0.5,random_state = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Lenovo\\Anaconda3\\lib\\site-packages\\sklearn\\linear_model\\logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
       "                   intercept_scaling=1, l1_ratio=None, max_iter=100,\n",
       "                   multi_class='warn', n_jobs=None, penalty='l2',\n",
       "                   random_state=None, solver='warn', tol=0.0001, verbose=0,\n",
       "                   warm_start=False)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr = LogisticRegression()\n",
    "lr.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.5, 0.5)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,6))\n",
    "plot_decision_regions(np.array(data.drop('y',axis=1)), np.array(data['y']), clf=lr, legend=2)\n",
    "plt.xlim(-0.5,0.5)\n",
    "plt.ylim(-0.5,0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training score is  0.528\n",
      "Testing Score is  0.556\n"
     ]
    }
   ],
   "source": [
    "print('Training score is ',lr.score(X_train,y_train))\n",
    "print('Testing Score is ',lr.score(X_test,y_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (e) Now fit a logistic regression model to the data using non-linear functions of X1 and X2 as predictors (e.g. X2 1 , X1×X2, log(X2), and so forth).\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['X1^2'] = data['X1']**2 \n",
    "data['X2^2'] = data['X2']**2\n",
    "data['X1X2'] = data['X1']*data['X2']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training score is  0.96\n",
      "Testing Score is  0.944\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Lenovo\\Anaconda3\\lib\\site-packages\\sklearn\\linear_model\\logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "X_train,X_test,y_train,y_test = train_test_split(data.drop('y',axis=1),data['y'],test_size = 0.5,random_state = 1)\n",
    "\n",
    "lr = LogisticRegression()\n",
    "lr.fit(X_train,y_train)\n",
    "\n",
    "print('Training score is ',lr.score(X_train,y_train))\n",
    "print('Testing Score is ',lr.score(X_test,y_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see from above that when we use the additional terms, the model reaches a test accuracy of 0.944, whereas earlier it was almost random guessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "preds = lr.predict(data.drop('y',axis=1))\n",
    "data['preds'] = preds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I couldn't figure out how to draw the dicision boundary here, but i plotted the predicted values, and we can see that these values are much much similar to the data we craeted. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x27e729766d8>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,6))\n",
    "sns.scatterplot(x = 'X1',y = 'X2',hue = 'preds',data =data,s = 50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (g) Fit a support vector classifier to the data with X1 and X2 as predictors. Obtain a class prediction for each training observation. Plot the observations, colored according to the predicted class labels.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "okay but before that, lets remove the additional features that were added in the last part"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop(['X1^2','X2^2','X1X2','preds'],axis = 1,inplace  = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train,X_test,y_train,y_test = train_test_split(data.drop('y',axis=1),data['y'],test_size = 0.5,random_state = 1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
       "    decision_function_shape='ovr', degree=3, gamma='auto_deprecated',\n",
       "    kernel='linear', max_iter=-1, probability=False, random_state=None,\n",
       "    shrinking=True, tol=0.001, verbose=False)"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "svc = SVC(kernel = 'linear')\n",
    "svc.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training score is  0.512\n",
      "Testing Score is  0.48\n"
     ]
    }
   ],
   "source": [
    "print('Training score is ',svc.score(X_train,y_train))\n",
    "print('Testing Score is ',svc.score(X_test,y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x27e73c84780>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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he7/3e/H+++939HMJISCUIvVoGVDabdwvF7GolBoS/oVTQX7lBbLPPqznklHOYY2MwcoOQ0mpvxtjoFWRVFIVB808+whe7lj3tssOX5n83S9crPitj4szSRIALb2Gg3AObouZSqNCWZPhGRufquebtZIbMdJDlwrxUsNAbGwS9sgYQGhPJrjLwEdlfwfu0QGgFHgihcTcYtuNyVouZFApgzAGZtr3tkmUga/nCUIAOlhSRA8RQinYgOQVtyIy0kJwT450vzjfq4vmWXesavvHf/xHLC8v4/HjxwCAH/qhH8Kf/MmfdNxIq9Ev4c0aUgSonGvIffaAhF8sNPwelDLgsgWTMYAxxManOnGobUcKARUE8PInICAwMlldyRtiUFlDI3CPD5rHh0cbns+sWKiMiz020awzRRnMoVF4F96X2bGe7hBwU2oJ6aXtdQSlIphlN3hh9XM4YpPTqOyelfqzWPxalcG9nMOnpIRzuAf3XE/VoFRAYfU10o+ftc2IUlLCL+a1jEnVk0sNA6ml5133LArXQXF9FaJSAgiBmR1GfGq27+bGiIdFZKRdwD05Qmlzrd5fTvqe/hu4k6G2tbWFubm5+t+zs7P4h3/4h7sd7CCjEN7bEIDq4X6Pd0VJiaBUQPHdm7PBnU2kHj/RrvwLhSDUsmGPT8HZ36mP1XTgzkM4R/rxc5Q2VxGUS1oRfnwKRirb/J6MIT4xDSgJ7+QYgAJPJHUOVh+Eya8LIQTMjiE5v9RgQJyHMg5reBxmdgRBuQxmaq23fj8PSgi4h83GvXQd7YVtl5EmAhTX3zaE2qXvo7y1jsT8o67l6NU0tGqCr1AK3skRCOOIR7IoDdQ8n8J1QJiWeurW9S4DH9LzEDhl8FhCS4s8cCM6MtIuUNndam4ArCQqu1t3MtLC+oz1str6fVMLYwblZjmDVk2PBwElApQ23l0cRWnjHdLL74FcNCI4hz02AWt4DCrwdRg3pKOENkhsJBeX6wumLp4IX5yoYSA+PYf45IyOml4i19HvXPW99OO8J3PKbo9q2fuwnTXPMghC+9v6hZzehHXJMStFcGagncM7PkRsbGJgpHjuSpjnk1k2Uo+fdlyIWgY+imtvEZTOKjaNdBaJ2YUHbahF24cLhPbqu2T8uszOzmJj46zcf3NzE9PT03d6z/tE9zX04RVycHMnkL537X6G18VIpWGdEyUkjCG5sDwQCf+tqO1iLyJ9r6UHkTIOZpq6GbR5efsgvSs2q83NL7/9KeOghqnfc0ANtAcLZTCzw03DhBttzdNqvQnoDaNI1cQFr4kUAYTnQXhuVxq8dxslAhTXGj2fwnVQ3t3SaRjVeV/6ftu/v18sNBhogBYeF5VyWz+nFapWRNNjzdujmfcC1DBDDbK7Tiqf+9zn8Pr1a6yurmJmZgZ/+Id/iN///d+/03t2gvOCp4TSlsm10nMbeqmBECQXl2G0sbqGcgOxyRnExqaglD6ey7w/gwChFCC0yZurS87DFxMphE5+lw/jHEXcHcqY9pL6HvxiXo+ZJpKLT9raUogwDp5MNelZxSamOt5z8zy1DcfFud0aGgXY9e4V6fsoba3pjiUT0zCSaXj5UzDTArNil4YEpdSdLZRU+h5t0V/4vhGe1xxJAuDnTqEmpxGUHZS31yFdFyyeQGJmQffhveN8U+sME4aXO4GR6qz2mfBclLc34Bdy1XVnGkYq2xOb0/s/gh4jNjnTkJMGQMs6TM7c6X055/i1X/s1fNd3fReEEPjxH/9xfPDBB3c82vYihUBQzKO0+a4qAKvbA9njkw3uZhnokFyDx0cplNbfIvP0g7aGDh6cNlK1wKGyt9UwHJsM7xcpgwDO0b7OSVMKoBSJ6Tndm7UHJpiI3oUaBhLzj7WBr1RVrqe9xgPlHMm5x3CO9uGdHoNUr++w/MpOQjhH6vFTFN+9gXAdALpCNzY+Va8EvwwpBMq7m3UDTUmp9QmrXNabVQY+3KMDVKqNwEm1KTpP9F4jcNLCi0ptGyoIGlrwiXIJ+TcvkHn24d17ZVYFi8N8c9SOQQaBvk4JAW3zJlT6PgorL+sGvPQ9lDbeIbmwBDMz1LbPuS3RLH6BWt5Zu6s7AeCrX/0qvvrVr975fTqFdnWfbyat4BzugccTjaERJUNzxZQQ2rh7uOkDd4ZSBmtkDDye0A3hCYE9NqGrM0MmJuGUG5oMQ0qUNteQeZoEIiMt4gpq+XYd/QzDQGx8CvbIeP3vblPrWpBaelZNyyAgjF6/cEEKLe5MKHgyjcI5Aw3QkYXK/g7iU3NN92lQLqFy7h5VQbUR+PMPey7PkTIOFos3hRjjU3Nw9kOq7ZWEnz8BG5240+cSQmANj8E93G+QxCGMw0xnkX/9iTaiKEVsbBLWyHjbNqHCc0OjZ5W9bfB48t6LhKJZPARraKQtRlm/4edPQ8ed4wPwVLphQgtreAzgUimMiOtBOQdNpcGqbYda5QhJKeAcNVfoAYB7coz41N28vxER7aJX5EjumoDOTLNljpRfyEONBw2RBCkCvdlqQsEv5HuuETg1DKQWl1He24GfO9ESNONToKbVMudYhvaHvs1nc6Sfvo/K3jZEpQwWTyA2PoXi+tszI0pKVPa2wexY27xcoesYUI0m3X9uWmSkRZxBwidRcmGcMI7YxDTK2+sN40ZmqCcm4kHhqgRuAtIyZERY7+W7RET0LdVCC7+QB20R2qOm2WIO7a97kRom4tOzwMQUAFIPgVvDo7oq9wLtMpYIoWCmhfj0vK4IZhR+7hSiXGp6rnO4D55ItcWbxu24Fv2+UCxgZod7okgtWlEj6hipTGhDdntsotGLRinM7DCSC0tgsYQWAZ2crTbrvv+L+qFAKIU9NhnyAIGZGYZwnY5U3UZEPDR0ocUseCIJAE06hAAQn5xtmv8o47BHx5vfkJCOJ8OHIYMAwnMhnOrc0KKKkVJW1wOsbQR5IgnzvOePEMSn59oeDqSMaX00ykJb2Wna6OHiDMmFJeCcg4EnkrBHJ3rC6fBgVlSlVE9W03Sam5QSU86RXnqO0sZqXcgwPjUDZsdDn2tmhvSkpdCz1UqDDjVNJOeXUNpZh/J90OpOtLK/UxXrZEjMLoIn01ELnIiBo7YB6cZiSg3dB1hJgeTiE7jHB/DzpzrnbmIG1LJDX8fjScSmZnVeWr0R+KOub2il76O4voKgpPOJCTeQerSsO4m0iKKch3ID8Vq1vQj08Xe4tRZPpkO9XPboRNvOH6UMRjKtm7f7vq6kZ6xntNlIL+mBtIPPfvaz6hvf+EbD2OrqKlKpFEZGRh6UIaGUwtHREQqFAh49enTt19V0YgipGV9X38BKKd1yiJDIm9Zl6udeKUgRoLy13lTYkXn+Uc8kKUsRAEJCykB7aAnVJfinR5BBACs7DGpa0XUU0RIpAkjXhVNta2WPjoNaVtc6GAA1uSIB0Kt7s9aljarOAsKNrq5FUgiUtzfgnRw2jBPGkXn6wb0nx7dCSYmgXEJpY1XnpREKe3wSdhsLB3oBQsg/K6U+G/bY4HzLS5idncXm5iYODsKTrAcZ27YxOzt7o9cQxs40t65hoMnAh3tyBO/kqF590658gYirIYSAGAZkEKC8sRFaeevnc2BhYZcuI4MAzuHuWaUYIVozizDd7QOAe7gHe3wa9th4VxfdXubMICAP/pxog/4E5a21+ph3eoT49DyobYNfoVnWLm5SDKGfe48CvlLAyx03DSsRQAZ+zxpphFLwRBLp5feq2p0EilL0W57fXXgQd7thGDfyJD1UtJq0B+dgF6JSAU+mYI+MXSrkK4MApa11BKUC7JFx8EQKSkkElRKMZOpaRl5E+2i5O++B3AoAEE6lsZRfKVR2t+siqqqqYu7sb8MaHn1YGnktkL4H53APXj4HVpUEopb9YMPXSgSo7G42jVf2tpCcX0L+7cu2NokfDAgIoVAIyU/t8ehSfRNa854e7EIpBXtkHCwWH3hnwGB/u3tAKQkVBAgqZSilYMQTfaMAL30f+defVEuPgaBchHdyhPTyey0nPCUFRKWE1MIyKge7qOxtgzAGa3gM3I6B9Ej7l4cA5Rz2+GRdQb4OoTB7oN+pkhLucbg328+fwkimtBZVFRl4dxfJrL2X71fbapGe6kN61gaMhIbNZOCj8PZVXYBVug78N3l9T1YlWh4aSqn6HNUwLrTYqXQdePlT2D0mb3GfEMZgj040iWRrY/9u90L99yDomJdXKQk/n0NpY7U+VhMWNodGqv2Ke+Oebjf3+q0IIf8TgP8Ler/820qpX2zxvO8H8EcAPqeU+kbYc3oF4TgorLw8E+QjBKlHT7W6dA/vWJSUcI/2myY/WW0b00o3TkmJ2OQsSltrEE5FjwkB52AXhFHYo5N9YaAOCsyOIzG7gPLuFlQQgNkxJGYXb92CR4oASggE5VK1j6d1ew8Faa1oThht6gXYjsRdpRSk515Qms8iMbNw754WGfhwDvfgHh5AKQkzO6wrBM8dl3Cd+nGfp7y7heTC44FdmC6DEBKq00gYrxcSBMU81NBIW+YeGejm7O7JISg3YA6NgHKjr+Y1QimskVEoJeuCsUYqg/gd7wMZ+PBOT+CeHIEwitj4lPZutfm6lEGA8s5G03hlfwc8mYJ/dAp7bLJnkv3byb3d4YQQBuDXAXwFwCaAfyKE/KlS6pMLz0sB+N8A/EP3j/JmSN9HaWO1QTEZSqG4/haZJ+/1tFdJKVU3si4SVMotjTTKGBQ3Ql/rHOzDGhrrq8ms36GcwxwagZHKVttEkVtPXDII4J4corJzFlpilo3U46e36mVLCIU9MgH3ogAvITDSQ3BWX9WHzOFRkDYII6sgQOHtqwZF8aBcQlApgym7flzdNtikFKjs78I9J3TqnRxBep42vqq/mfSaldABvXmCVA8yHEwYR3xmHqX1tw3j8amZuqeWxxOhYTyl1Fl7oWu1g9JitM7+Tn2ssr+D9PJz8Fh/eTIpP9/5QVU9t7c3AWqpLv65npuFYgGJ+ccwM0Ntc0pI34PyfV0cdRGlABA4RwcwM8ORkdZm/jsAb5RSbwGAEPKHAP4DgE8uPO//APB/AvhP3T28y5GBXy8LroUzlZKhxooK/J7XqiKUwkhlwsUK0631fPR3D+u4hqqxOljVw/0AIRTEuLthrKRoMNAA7dlxDvZ0L9FbGN/EMJB6/BSlrXVI1wGzY9XdPIeVHYEMfFjDo+DxRFtCkkoEDQYa4RyphSWUdzfrUgTMjiG5uNzd6lchmo1VAEGp0DBX8BYhTTOVaemVHHRqc1Xm6QdwTg4BpWCmh+DnT6uSGKYWIr1gJGivzzG83CmoaWolfcO89DpWQjYYaHpQoby1juTict8ZBe3s/KCkaDDQalR2NmEkUiBt2PjIwEfh3QpiYxOgpgXpuQ2P1+QyUotPmjzxg8J9GmkzAM77LzcB/Pfnn0AI+XYAc0qp/5cQ0tJII4T8JICfBID5+fkOHOoZtfBJaWMVQbmkY/1jk7CGx7QbnrJGT1qNHvcmEUJgZobgHh80GJpGMhMq3Fh/HaUghhEafjCzwz3ZJqqWBxRUyiCUgVn2vYe+epEgROkbALyCDi1cnOxrUiA1TwWhLETck4Em00g/fgZtwJP6uY9Pz0FBXcvDcX0aF2p7dAKV/Z26gQboYobiuzdIPXra3etAtdi4nZNFIpzDnphu6M9KLRv2WG8Ibd4XlDGAxZCYmoMMAni5YwjPRWxyFtbQcJOnV/o+imsrZ5XPJcA7PUZ6+T3wWLMOZA3VYuEPKuVLhFYfBmF5gQBC+2De+jMCnfPsHO0jPjWL4tpbnN/4xyZn4Oxtw8udwBod1702eyTftF3c57cJ84XWzz7RZYG/AuB/ueqNlFK/BeC3AK2T1qbjC/+swEd+5UXd9aqEQGV3C4QbMLNDsMcn61ICNczh/gj5UcNA6tFTCKeMoFIGT6TALOvK3SLlHKlHT1BYfV031Hg8gfjkTM9VoCkp4ZcKKL57c+YJNQykHz8Hs3pDR6xXaBXSpNxsCiXVwuXFd2/qk7SRTGvRzhDDJ2yMUNr2wnrCWMMOnCeSTfcnoA011cpouiEyCLQBdpnQJ6EwkummIg/t2Tl7TU2x3soOn+UFRpuKBjcxlkYAACAASURBVCjnsIbHdAI5oaFhNhn4zdI0SqGyu4nEfOvcvla5nMyO9XxVZKehXGscXtxs8ESqbeem5vAISkV4poX08jP4xYLOqUtm4OdP4VW9ee7hPqzhschIayObAObO/T0LYPvc3ykAHwL4q+pNNwngTwkh33ufxQPCdUNj4+7BLsxURl8khqmb6iqlJ4/sUN8k+FLDADUyN2pZQggFi8WRefoBpAiqib29o9h8HiUClNbeNuyCle+jtLWG5PzjgbvB7wIzLVDLhryQuB6bnGk6TyrwUVh91XBv+MU8ynvbiE/Pttk7dn1oLby6/lZ7Bju4hVNSQrgOyjubkK4DnkxpJXqjWbiUco747AKKq6/rhQGEG0g+etJkGFDGAcbBWijaR1SLCUjrayys+EKPu5fm9hHGYI2MXQhNE63J1oPzWzchjCMxt9iQG0gY00U57eoGYBg6CiUlvJMjeKfHSD1+Ci93isK717rH5zmCYgH8kshPP3KfK9I/AXhCCHkEYAvADwH4n2sPKqVyAEZrfxNC/grAf7rv6s5Wu+1a5wbKOayhERipdNvbJcnAh/BcSMcBq+bs9MpEUdOy6fUdvhRBaDg6KOYffPjiItQwkH78FJX9XfiFHGhVoyss/C2DIHTz4p0eIT4xda9hb2ZaSC4uV3O9dFjfu5BLw+PJO3u7peci//pT1CxB7+QIfiHfsmiImRZSj59BCaHDvIx1XYn+odAqpMkTyUtTUSjjWuYhnYV7fAjCDdij423Jt+p36rmBzz+CXyyAMqbvozZudAnTfTWL71a0x04p+KWS9oyH5HnTHumq0k7uzUhTSgWEkP8VwP8HvY/5f5RS/04I+XkA31BK/el9HdtlcDsW6uKtabXUaLfxJAMfxXdvGvKEzKERxKdme8ZQ6wdaVQyS6ByGQg0T8alZqPGpy1t+tTAsekXM+Pw9Ep+eB0DqCuw6LLt4p/tIV2vu4KKrTgU+/FIRVnY4/LgMA4gW/I5DGIc1Mg73aP9sjBuITUxfmZJBuQGaylTDeL1zTXcLKYTO4S0VQRgHj8XqmwmdG8jAhjtjHBHKYCRSyD7/EMJ16xEalc4gl8/h/P1GTRMsNlheNOCeddKUUv8VwH+9MPa/t3ju/9iNY7oKwjhSj5+guLZS9xwYmSHYI53LO1NKwcudNiVyeydHuiNAZGBcG0LDc4FiE9Nt3QEOEtepCKOMg1oWpNtYfWWNjIH0WKifGgbis/OIT8/q0gXSBnHbareOMC5WpEV0H8q1R8waHtVeYdOCkUjeSEqmF/KKZRDUK5apaYOwu8loXIWSEn4hdyGkyZFeft618Hutpdb530oxhvST56jsbkN4LoxECtbwCES5BJrqD/H469Jbs2cfQCgFjyeQefJBtYqNdlzBvFWpMwB4+Rx4PNmxzx40KDeQmHsE52gf3ukxCKWwx6dgJNNRmOkO1IpOSpvvEBQLAKGwRsZ0aKgHJ0yd59W+9yOUwcwMNVSN1rhJfmdE59DpIfzSas5eRgY+Suvv4BfPZJJik7OwRkY7p/QvApQ23jWPba3faw6vkgLlvR0Y8QSMdAaiUkH+7StAAdnnH96pT2qt+l+4Lkj1mrlPR0hkpN2CMx2q7vxwhNCWsfaoIvHmUOO8qGN4pWHEzWGmheT80lkqAGP3VjDQbQghMLPD8E5PGqoI7bGJWwn/RkScpxZNOW+gAUBldxNmOgt0yEirVypfQOfw3q4auuYNVFKCcn67tolKIcifIsifNr+/EKC3nNKlFAgKeRTXz4rLWCyO1OLyvd3HkZHWY0ghdEIko/UFTnt7JuFWhRtrEG7ASEa79NvQTlHHiDMecnUs5QaSi0uQvg/hujp3h/EHfU4i2oMSAt7JUehjfiEHZncm9NhKMFkbLDePPEjfR3FjVRt5AEApkvOPwZOpG27oCKhhhqYY3KlTiRANBhoAiEoZlf0dxKfm7mXNiFapHqFWvl/afIfC25cob29CeN65qlEDmacfwEgPgVk2rJGxSxufR0REdB/KDfBYHFZW36eRgRbRFghpmTPbyUpTQpluMXeB2OTMjXN4lZRwjvbPDDQAkBLFtRUgCBfGbXlcnCM2Nds0bg6NgrDbmzWBUwmt8vdyp5AipC1VF4hmkC5x5jYmobIcMvCRe/VJ3YUsXAd+/gSZJ++DVFuXMMtGYm6xydPWi2iPoIAMgro7O1qwIiIiIm4OZQyxiWn4F8J7hHEYic7lJFPOkZhbgHuShHdypDvsjE+BxxI3zuFVQsA7PQ55QCFwyjDNGxRxEAIjlUZq6Tmc/R0oKWENj8JIpe+Un9fqtbSNUlo3JVo1O4xSCtJ1dUJ1uQjCDcQnZ2Cks3WjRUlZFb9tjPGrIIBXyMMersvF1UueexkZBHCPD1DZ267vSuzRCdjjk1ElakREBIDw1I6I1tCqrl55ZwPSc8ETSR2C6/CcSrkBe3QCVnbkchmea9AqfHqbECVlHDSRBJt/DCjVFicANcxwAe+J6XtbuyIjrcPoNlKf1vucqcBHafMdkotP6o3La4ZcGGEN23sd6blNrXecwz1d5WYrKKV0MUQUqo2IeHAoKSF9D+XdLUinApZIVZudD5aQrwx8KKm0hOBlLcKuie57m0Lq0RO9+W3De16Xmlj5XagVbBXXVprG71IAd9tzIEUA6fvwcieg3ICZyoAYHOnHT1He3YKfP61r6fFE6tbHd1ciI63DBJVyaCNaZ38HvNo1gFAKI5OFX8g1Pc/MNOcD9DpuiwRX9/gAxDDhHu6BWjaS84/ArFiUwB8R8YAIT+04bdmZod9QSkF6Lkobq1rbkhBYI2PaEG2DN6afoxE8kUJidhGVvS1I34eRyiA+M9/1ykkpBNzjQ1R2NutjZUqRWX4PzI5pwevJGbRKT+omkZHWJqTv68TCqtu1psgcZqABtcax1QbfhMBMZ+HFjxrK983scF/262uZ4MpY/XxI10F+5SWyz+6maRMxeEgh9P0hpa7CvU2JfkRPoqSEcxCW2uE3pXb0KyoIUHj76qzyUCm4h/ugjMMem3zQ1zLlHObQyJl2ICX309daClR2ti6MSa3/trCkQ6c9klYUGWk3QCkFFfjVHoA6jk4NA8Jz9U1ZVRYnnCO1+ATgRks3qTU82qDEXi/f9zwIpwIWi+v4eB8m21tDI3D2d5qqZMzsSKOrW0r45SKsTHjLnIiHhwwCOAe71RxNBUIZ4jPzOoezjZOm9H0ElTKEW4GRSIGaZl97KPqFmpcpjIt5QG393KpAqeqC4S8DP1Qawjk60PP+A9+UtiN0eleE7+FiCzcA2klyS/23TtF/FsA9ofPGHBRWX9dvQBaLI7mwjPL2RsPEo4IAxbUVxGfmoYRAaukZCquv6w1hjcwQzMxwkwuVckOX8McT3ftiHYByA+ml5yhtrUFUymCWjdjkDLzTI6iLZcwyamoecUZQLsI52K3/raRAaWMVmWcf3nhnK/3qhqraY7CWtCx9H/m3L+tGQQXaax2fnuuooSYvbvD6cAN2VwilMNLhqR1GujOpHVII+IU8yltrev6hFLGJGVhDI535DUIkHM7GByfnrp9pdZ/ryFVv/UYPb5a4JSoIGgw0QIvclbfWwOOJxtJoQoDqbq24toLMsw/ryZ6EUvilIoTr3Husu1PUWmfp76zHgkoJ7vHhhScSGPeYkBnRW0gh4B4dhD7m5U4QG5+61vvUN1RrK3VDrGaEEcrgHh80eW2802PYoxMdM9KE56K4tgJRKQMAeDKN5Nzig+tGUE/tOLmY2jHSse4pKvBRWm/04Fd2Nqo5we2Xr6CGAcJ404bUGhppWd0Y0V0IZdUOIY2SIPHpuZ4raIuMtGuipAh1YfuFHOyxyfrf9tgkzHRWi+IBSM4/hnAqKG2+qzdkB3S3gEFJlG3F+QWPkwSskXG4xwfaWOUGkvOPWuavSSG0W/wB5288SFpsWm5yHaggQP7ty4b7zTs9BjVN2CMT8Av5hucTboBZNoJKqSNebBn4KL5701CpHRTzOv9l7tGDW7ipcSG1Ix6vRxE6QctCpsM98Fi87XMM4QZSj5+iuLZSj7AY6SHY4w87H62XoJwjPj0HI52Fd3xY139r1X7xPomMtOvSyuNFaH2StcenQAhBfuVF/WFmx5BcXIa6ENY7n9v2EKDcQGxyRhu0qpoXwjkIaZy0ZODDLxa0cCLniI1Ngpjmg9RRqvW4k74HalogjN1Pkm2XoIzBHptsEuwEITcKhcnAazDQarhHh7BHJkAtGygXAUKRmJkH4QZEpQRqWJC+3/adtJIyVErHz59CSTGQRppSEqqmIh+irdXV1I6Wc3fzuJRCFzdVox63MRwJIWB2DOml5/r3JRSIxLx7DsoNWNlhGKm0vkZ7dI2JrpprokN4yQYXPVAtACAE9vg0jFQahXMGGqB1ztyjA5iZbFPvtYsGyqBzlRCvDAKUttbh507qY97JEVJLz0E7qKrdi8jAbzoX9vgk7NHJgZ7smW0jMfcI5Z1NqMAHtWwkZhdvuFi2WpQBQCE2PgXv9BiJ2Xl4+VzDOWZ2DKlHT7sU8hi8VAdA38de7hiVvR2owIeRTCM+uwB2T14KKzsMZ2+7adwenWjwbMnAh3OwB+dwH1BS5xzPP9YbpBumpZwlx7fvOqrnNBKiN2w9alT0G72+8X1YVsIdoNxAcuExjPSQHiAU1ug4zHQWuTefAtU8mDD8/GnTjtEcGgHu0GNsEFEiaFgwa1R2NiAD/x6O6P7wi4Wmc+Hs74aG3AcJyjjM7DAyT95D5vlHSD9+BiORvFGYqCaBcxFreEw3PDd0H1zCjaZzLJwK3NOjes/cdkAoBYvFm8bN7BAwYAutUgp+IYfy1jpU9Z71i3kUVl5C+vdzDxNuILn4BMQwYaQyMEfGkFx4DHouB04pBffkSBet1PTbKmXkV17Wv8d9oZSCcCoorL5G7sW/IffiW3D2dh7cnPhQiayEG0ANE4m5BWTf+xiZZx8ACii801Wb3ukR0GIhIYYJZsfB7BioZSM2NYv41GzPW/DdppUBIhyndcXUACKFaPK61vByIb3vBoiazI17coTK7haCcvHGixHhBtJLz8DsWHWAwBwehT06rsPslIJZlhYaDcHP56o6hu1Bb/CWG+R4jPQQ4lNzXVOM7xZKBA3VuTWk70G0kN7oNJQx8GQK6aVn4IkkICRAaENluQoCuIf7Ta9VgQ/h3e/GSHeteVkvOoGScA524Z0et3UzEdGbRFbCDaGMA0yrZLtHZze19D3dS8y0mnSAYpPT4LEEUo+eAsDAVnXelVZJmzyeaGkADyKX6QhRPriFJoC+j/KvP61Xxnmnx+CJlPZ8XDPkSQgBs2ykHj/VuliEhLbQ4TUj7gLMstueisBME8mFperx6OqyQcxFg1KtBbxFgMCpQLouWCzW1RxLFfjIv/6kfmze6RGMVAaJuVooXSFMN6v66q4cYyuE5zZLFwFwDve1lFOPVSNGtJfISLslhOpkUJxL/i9trSE5/xju8QH8Qh7UNBGbnNWtj3pAwK/XIVRX2Dj7Ow1j8Zn5B+V1JJQiNjYJ7/gI5xcIQllftgm7LkpKOPu7TQtSUCpAuO6Nk7ivej6PJ0FNE/K8p4TQjlXhDWIuYa0Pp3t8BCUDWCPjMLPDzd40QkC5gfyrf68PxaZmYQ2Ndvy8SCFQ2dtuMh79Qk4XinAtmWEOjTbMPYDuknJfuXR1LtVdizxpg87gzRpdgjCO+OQMytsb9THpuZC+h9jUHGIToj4xRVwPyjns0QmYmSHd9NYwYKazoflFgw4xDKSXn6O8vQHhVsDjCcSn5wf6XCgpEFTCQ5CiUobR5uIRamjRZedoH36hAGbbiI1PR/fsDQgqJRRWXqFmLLjHh0g/eR9BpYygqKVOCGVIzD1qMtwqO5sw00PALYy0egcBpfQG+LIOAlKehQovICqlugyHPToO6bl17SxqmEguLrWUCeoWzLJBKGsKwVsjjV1rIgaT6Be+JYRSmNkR8HgSztE+SLWQgBrmlVWMEa2hnINyDh6SaP2QoJSBxhNILi7rRGZKB96bSCgDjydCF9SwxPt2QA0TsfFp2KNCn+MBS+TvJDLwUd5cQ4M3RykU3r5Eevk9/acUIJTDOdiBF1IUFJQKNxaxvdhBgFCG2NQszOxQ+D1SLdwIk0FhsbOCLsoNxGfmEZ+chVJSh6R7IDWFMH6mu1bN2zWHRnQhzANKA3moDPas32FqBkUitgCA3PvNHDF4DGKIrBWEUthjU/BOTxpCnjyR6pgafe1zB2Wxk0LrfAmnrLXIDLNzciJKQYRUtKtA98is5fxJEUC64UUDt+m4oPzGDgJKCt35JRYHjTffL5QxxCamtS7duZAnT6abzk0t57iXqFUHp5ff0940SnVbscgR8CB4OCtAB+lFvTNVS+Ct9i3sd2QQQFWFJinnQKQTNJBoeYz34Z4cQzhlmJkhnTsWhSCvRAoBL3dc9W5ptO7bkw61nyKhhVIX5xzKOGKTM/DfNHZ6oIZ5VoF7A9yTw9Bx53APidnFUIObGibSTz6Ad3II4Tr6ukr0z3XVCd21iP4gMtIGEOn78E6P4OVOQKpK//UwbA9SU9b38zkQxmCk0iDcqHsmm4RdCUFidhFGOtuz3ynidujFyERsfLKebxRxPZQIGgw0QOu+VfZ3EZ+a7UD7I474zAKKq68axu2xySb9N2rZSC09Q2VnC9J3wZMZxCamu9YnkRACZpqITUzrCts7notaTlzgVHRV/w09llIEdQmQXgipRvQukZE2YMjAR3FtpaEzgp8/RXr5PdButGC5IXr3f4Ly1tniQihDevk5mB2DUgpe7qRRdFQplDZWkXn+0Z1z/2o6Q52aJKXvIygX4eVPwWMJmJnsg2uqfVvOjHRtxAunAmpZHe3z2M+ISnPOFVBtPzU+CULbe90RQsDjCWSefgi/lAcUwOJxMNNu2jxRxkATKbDFZV2VSOmtN1jW0GioFtvFDgItj7sNBppfzKO4tlKvvKSmhdTjZ2Dm1edYuC7KW2vwi3lQw0BsYkZvOB9QakPE9em9OF3EnagZBRcp72xChvQzvHekQHl7vWFISYHS1lp9cXaPw4Vd/WI+dPx6HysgnArK2xsob60jqJT17raNSN9HcX0FxbUVeCdHKG+vI/f604HvGtBOZBCgsreN3Mtvobi2gvyrT1BcX43U1kNo5cmhhqHFWzuA1qAjkL4P4TpXbnYo1x0f7uIBJ4aB5MJZ1SVhDPGZhYYOAjdBCgGlrt9HWYkAxbW3DdIY0nNR3tmAbKERV3+e7yO/8qI+d0nfR2nzHYJS4VbHHjH4RKb7HZCBD+n78It5MMsGjyVu7L6XgQ9VnSQo45eXkl/n/VqoekvPqbc76SWk74fqAAWlYnXHTVqKft62/FwphaBYQHHtTX3MPT5AfGYB1tBI28JCwnX09zj/2YEP53AfsYnpgUlW7yTScxtEowEgKObhF3Kwhka7eyxC6BBXqQjCOHgs1hCWv2+oYYJadlN7OntipmNemqBSRuHty/o97B7tIzY5C2tkrGOpCJQxGOkMMvH3ryfB0QLp+/ALOXj5UzDThjU6pjXTrngf4Xuhc6lfyAFSXOrdF24ltM1UZX+3r3LkIrpHZKTdEhn4KO9uwTs+S2KlpoX00rNrh7Ok3xiaJIwhubgMHkvcegFvJVXAE6mmPBEphBbjpeTe5B1aaRBRy9b/Zxyx8SkULnjNCGMwbhm+VYGP0tZa03h5ZwNmOtO2sFCYR7M2HpYXUzPYhedqbaQuKrJ3Cun72kvpuTCSKRBu3Mhg8PLNsg0A4J2ewEgPdS0nUUoBP3+K0sZqfYxwjvTSc7DqtXrfUMNA+vFTVPZ34OdPQbiJ2ORMx+RspO/rNIULm6zK3hasoeGOyhARQkHukDZwMS3EB+Ac7yPz5P0rf09KW8xZ3ABwucHeshuDDB5U67uI69PfK8A9IgO/wUAD9K7/ul4S4XuQvg8jnYH0XUhfL9DF1TfIPPvg1oYCYSGq/bXigeqkqZSC9L1qb8QSmB1DfHIW1DS77t0hlMHMDtcFJGvEp2brXkkWiyE5v4Ty7iak54InUkjMLNxa2LXWH7IJKaFk+7yNPBZuRIYZ4TLwUdpcg58/rY/ZY5Owxyb7NldF+h7yb140hHft8SnYYxPXNj6pER7CIkaXPVhCoLT5rmFIBQHK2xtIzD/qGWOaGiZiU7OIjU8D5OquC3dDhWqPQSlIIUB72CkkXbd5EyUlKnvbOnR6iYFJuNbzu9j7NTYxfaXwLY8noA25RoPMzI5EwrQRoURXxS0JiuFeEr+Yhz3WOoFVBgGCchGVnU0Iz4ORTCExv6SV5SslKCkgfO/WyeWUadV+Kztcb03F48mGMOzFPnbSc5Er5JF59kHXW6BQzhGfnoORSsM9PgJhDLHxqYb8Eso4jEwW6UQSgAIIvZPhQggB4UazodZmvSxmx8BiCYhzKvqEcVghCc5+sdBgoAGAc7ALMzsc+l2l7+sOF0JoPSreW5IkUgqU93aa8u+c/R1YQyPANRckM51BZZc3tooiBLGxzrRuakWrsLxfzGtvdO+cen0ddOVaIKCWFaKB1vuyP4EbXmQhnEr192x9/JQbSC4s6ybnuWMQxhGbmNb3ulOBcCpgsXhVR/OCpcoYkgtLKG68rbcU5Mk07EiYNqIFkZF2S5gd7hJnpn1pkq5wKyi+O8uF8gs5BOUSkotLKKy8BHD36iPKOcB5Sw0iL3fS7HZXEs7hPuJTM13XfaPcgDU0CiOdRasJvp29Twk3kJiZ19VZ54hPzbV1N0sNA6nFZfjFHPx8DiwW1zlvFyZuKQS8k/DiCO/0uClcJTwPhbcvz/IPCUFy7jF4Ot07hpqQ9bZAFwkq5WuHCAk3kF5+D+XdTYhyCdSyq17W7lbItsqL1MfRGzlp3YYaBhIzCyi8vSDBMT7RMSNRe8EDAOpO+butvNwsngTY1e9JDR2dsMcmgKpHt7i+2nDNm9kRxKdnGww1SrXEUPbZh5BBAMIYCKUDmYsmg0BHJ3qoe0M/Ehlpt4RZMTA71ujuJwSxyemWu0gpAjh7O03jSgQQrlOXnKCsszdsmEo4UC06ULi3NadbISNCCHgyjczTD+Ac7QNK6URn02r7bpYa2gA1M8MACe9KcZkBSi+U9EshUKmGfesoheLGW2Sff3StxVFKAUilF4iQ41FKVh2WdzgXpIXQKXAjby0hBMyykJhd1EnZd/Si3hbCGIxkBn4x1zAen5y9996O9wmLaQkO53APSgpYw2NgdqwjnjQZBPDzp3AOdqGkhDk0Ant0/FYGDjUMGJmhBmkfwnX+63U3OrpThb4/3dPjpk2Jd3oEa3gUNGmEvm6QpXh0+sY6/GpOqe6DugxmxyJD7YY83NnljlDDQOrRU7gnh/DzOVDL0jf4Zd4ehZYyDyoQ4KkM7JHxjgs8mplhuEcHzePZ4Z5yuWvBRwl0oAWK7q8aQ3x6HkDndNJqXHZeCaWIjU3COz7C+VwVwhjMdLbxyVLAzzcaCgB0ix7PvXTiV1LqXMT9HZ3In8rAGhqtX29KCsgggHO4B+l5sIZGmkLl14VyjvjkDPIXVOZZLH6rxem+++FSbiAxvwj3+Aje6ZEOcY1PgcXjD3rRqf0u8Zm5uxv2l6CkhHtyiMrOZn3M2d+BqFSQmFu8seFOq950MTIOL3cCZsd00dAtDD4pRVNObQ0vdwwjmbrxe/YqSkqoIIBfLoJQqpvTX6hwVlLCOdirG2iAzk8tvH2FzNP371Tw8RCJjLQ7QA0D9tgErOExXSF5xQ6MMAYrO4JySANpM5PV5d9dWIiYbcPMjsA7PQux8WQaRqI3JhMlZVV3aBPCqYAnkvWuCe1eEHtlgaWGifTyc5R3NiAcBzyeQHx6LmTR0F435TZXiV0VqpW+h9yrf6/nVgWlIrzTY6QePQU1DAjPQ/71J/XH/fwpjEwWiZmF23krbBvpJ++jsrcN6XswM0MNRmG/QXn1fh8a0Z7CB+xBA2qt5/Smk3Kjox54JYKGYqgafuH01sU+lBugSePORhQhpKVGW69U/rYDpSSCchGF1df1OYJQhtTSs4aUDK1t2dy6S4kA0vcH2oPYCR72LNMGCKEg/Hq7R0IIzKFh+FWdp+og4tPzOl7fJU8B5Qbi03Owxyd1kqtla4HJHsmLkIGP3DljwTs9hl/IIfP0g4HdhRFKweMJJBeWtQYTpaHhX8J1knJp/W3DOIslLjUapBCo7G03Jb8LpwLhVgBCUN7eaHrcz51CTcwCtzHSKAONxZGYewQoWQ2v9o6n9ja0Mzeyn5GBDy93Cvf4AIQQ2GOT4IlURw3XVvIVkJcLyNZfLyWUFDo/qo0eP0Io7JFxuIcHDfpphDGYmaG2fc59owKB4nqjiK+SAqWNVaQePz23fpB6nl4TPbIp7iciI63LUG4gMbcIJXRoiZlmR8J5Vx8HB+VcVwb2EDVX+UVjQQkBL3cKe3T8no6sO1y1yBFCYCTTSC4sobK/AxUEMDNDVamOy0LtsmUuonCc5vzK84+7FZDq9XIb9LXdIwUNEXdGCoHyzha8c43Oi2sriE3Nak9pJww1QsETqSZlfsKu3tzWJIecg10ElTKMeBLW6ARoG2VcKDeQefr+mfc/nkBscubWMkG9iJKiWrTRiHAqULIxTcMeHUdld6vhedQwH7z3+TZEZ+weoNwAuAHWYbULKQSgWieI3/j9Av9c373mS6cWdrjLLrU2oYYhWnRTeGhQzmFmhsDjWpLkOlVuhDIYyRRESKidJ5IgROeX1D2851/LOco7m4hPzfSMtzXiHhGiwUCr4ezvwEimtT5bm4uAKOdIzC4gv/LyTDqHUN0e6sowf6PkkCiX4J4eI/PkvbZ55gmlYJaNxNxix/Jo75tWXnC9vpz7m1JYw6OQQaBzn5UEiyeQnHt0I6O1nAeLywAAIABJREFU1sS+Jvx91248/UpkpA0gUghIz0VlbxtKBDCzI/Wct9u+n3DKKG9vaDHZeBLx6TldDUkIpAggXRfOofaAWaPjYFbsVrsmyhjM7FCTZhiAgQodtIOb5HYRSmGPTsDLnUB6Z0awOTSiPQqMIT49h/zrItS58JE5NIKgXIJ3cggznYl+gy4hA7/au1aAmWZPLVCt+lwqIfQ/P7i2Dt5NoKaFzJP3IDwPSkpw265LWLQ+VgX35LApVKqq4dp2e+Yp44PrNKYU5vBok4i7PT7VZChTbiA2Oa0lShRAKLnR+iODQBeK7G0DUtb7sxqpzKXGr+6iI6rtwmjf5r+eJzLSBhBRKTVoFwWlIvxCDonZ2yWAS8+ta7gBWtst/6aEzNP3Acbh504b1Ni93AliU3OwR64n0Kg9frKeK2Ik0zBSmQavjjk8CnbLBsoRGmqYSC+9h6BcgnArMJJpUNOqG9PUtJB59gHckyNIz4ORSkMJUW+h5R4fgifTPe0hqFcEg/TEBF1r9VX3aF+j16f0fRTevTkTQSYEyfnH4Kn26uDVPBVSnOVpXWdjVfNqqAuV6iwWh/RcBJUSYvZk246z/rmEgBg3lK5QLboiABBOs1c5ojW1im1ux+EeHwDVjZ+RTIfO83cRVRZupaGSVwmB0vpbZJ592LLKW7dq3NZeXqXALBvJhSVQy+6ZArHbEBlpA4YMfJTPXdw1/PwplLh5Ang94fwCSgTwiwUYyVTo51X2tmBlhy5tb6WkgPQ8lPe2IV0HRjKtWwYZJhJzi5C+D+G54HYMhN0+JyriDGoYMDNZANmmx2qLILNsCKeiPafnQs+9LkYpPBfl7U0ERd1pIzY5o5tWt9Gro5QCoK5VACE9D4W1N/UQM+EGUo+eXKoVpaRE5WCnoUsFlEJx/fo6eNdBimov0s21erK7OTR6rZA2YRyJ+UdalPtclV98ahbl7Q3Y4+030G4LoRRmOtOgh1bDuChvE3EllBuwRsZgZocAdKbCWUktrB6Ge3KE+ORM6GvcowN4x2fSUsJ1kH/7EpknH/R1sU+06g0aSrUWqw38W5SEq6Yd8/n3O1+G3/jg1X0wpd9YxSmcCrz8CdJL79WrTTvWHLrqFh/E3JG7wmIJeBur9bY1NbrdiukmSN9HYeVl3agUju7skXr8FDSZvvv7CwHpe3AP96GU1HqG57yQYc8vba835ACqwEfh3Wtklt9vuWgoEcALMSigFAKnArNNOVRKBA3N4gHAOzmEkUjCGh699LWEUhiJFDLPPtSafYSA2TFU9rZ0P+IekfKpYaQyTb02eTLdsutAxOXU2up19DNaf3josBIBnONm7U8VBJC+1xNe9dsSGWmDBqUwEkn4heaWPK2aVV+GboA+gqDU3KvUTGW0RpBh6N6G5193Ra6IlAKV/Z2mKk7peQgqJZhGZ3a5SkoIz9W9U10HPJFCbGKq6z1LexnKuW7FtLWOoFwCs22t2dbD8ifCrYQWnFT2tsHs+J12/EopBMV8Qxsx7+QIsem51j0XpQjNq1R+NfzZatEgBJRxiAv3E9DeZPxQQWQA3ukJeCoDUm090sp7Wgt5sngCzsEuKjub4Ikk0svPe66isdZrU7gORKUMFk+AWVZUBNOjEEphj02Gblas7PCN30+F9NztJyIjbcCgjCM+PY/8m08bkmVjU7O30mEjhMDMZOEXThsm9lp5uU7oXETx3euG18VnFi6vupIqpDGzRrgVhIXj2oH0GwVbPc/VGmxP3u/r3VY7IZSC2zEkF5aqobDeyO+6DOm36uQRhDZGvwkq8FHaWm8ar+xuwcpcEtKntMkbqcdbh4wpNxCbmG7qK0tNq60ioGFzAbUsxKamUdnZgJ/PgRgG4hPTOg8xxMiljIHGE2DT8wBaV333AtQwdCuoAVL/H2RotRVceWcTSgSghon47ELLDQBhHNbwGJwLqTmEcS1z1cf05h0VAaAWkqsJm17fwKKmhczTD+AXC5CBDzOVBTH4rcN6lBtIzD6qKkZ7oKYNws4mZJ5IIvPsQ7inx7q6MzsCYhiXt0JiFEY6g6Dc7KEzkplbHedVKClDvXcq8OGXCrfapQ0y/ZQDyBPhoSsjO3xnkWjd1LvZs3VZSJ8wDntkHM7BbuNxxhNXhox5IoXE/CNUdrehggBGOoP45GxbDWUjmWoyIuNT8yiuva33W1WuFi9NLixdWtXb6wZ8RP9BGYeZHdbFS9VKzctyYgmlsEfGIH0P3skRoBSoZSO1sNRznt2b0j+z8ANCKakT6ne3ICrlujDiddsi1RLAraGRth0T5RzgPDSnrd6/b2L62u9HCIU1NArv9Lih+soc7lzboNp5DaOVVy+iPyCMIzG7qCtRq0Y4jyf/f/beK0a27k3velbYsXLnHE73CV8agfxnBnGBQbKlERLMBcGDZcGFxQiEJUu+wRjJQr5BmFtsiUEYEDdGBKERGssIzCVhLIwYz/f/Tj6dc6i441qLi7WruqurqmPF7vrdfN/ZVd21u2rX2u96w/Pce8L41t9NKKhhtpZTKe34u3XJZhYgRPexSQkzX4A7v3RnmU3r4E3ASGWhM1Td75sk9ZL27rekpO2CUNoI0K7jHR/oAYwRv9mNGS2uG9jfB8oNuPPLcGcXxhIcY3qLjGLdUJ/schsluWdmi1Q3qReBn/SH6RtBrzI4hDKYuXyLajkAGNneZO+eK/Us7129h/2CMgYjV0A+k4UIgoZDQjcCC8I53MUVPc14DXd++daSPuUGnJl52JPT9ZO8d7DVa/spQpKS9tpmEtQSxNcnSq/RjZLxmDH9oJ4weE6Mg7QhQymlNWhulFGUEAguzuEM0Xh7N+hnrwghBGZ+AuHledOklzU5Mzb9vScN2ZTDPcjAB09n4MzM9/390yXIWAvvJhktLSTKun4uhBDwVAa5Nz/qCTIlYU1Mg3CuJ5zjWO/Y2wRhD80G9JvrQSxXLvRcXXNAZuYKd6r6jxkzpjeMv3nDhlJtSw6AbqjXadzh1arqNVIKQAg9BfcY029uIL22CRmGWoPNce/UYBNh2GigJ/R5pNAfS4tsSuAjKhWR3fyub++LkhKxV0Vl60vSK0ZgTkzBnVvoWUmuvkNPLSwD0PIz1b3tK/0tQuDOL8PMT4xUL18TjCG9so7KztfG58ucFOwhll4ZM+a5M6KryfOFUAozV0B4ed7ymJWf0DZM9QyCwosKGmQUona4j6hcBLNtOPNLoIldzkNuzrqkaoC7d+skicBHZftLQ++KpzJILa+P/MTQY+g0eCGjEFGtDCvXn8ELJWKUv3xsiLACCuH5CbjtwJqc7vkmRimFsFRsFkhVCrX9bRiZLDCiQRplDDybQ/7dTxBh0Ni8jHvRxowZHKO5mjxzeCrdYotk5PLadiUKUdn5irii+6qYZSO9tvkIkdrRQkYRSl8+QAY+mO3AnV2Ef3yIqFoGNSy480tgjtvVBmsRhk0BGgDE1TJqe1tILa+PbsbkkQzL4EVcq10L0K4Izk90aa7HmxYlhJ4ga0NUKoJNj+53sW7lMy7/jxl1HquOMGwMNIdNCPltQsh7QsgnQshfbfP4XyGE/EwI+f8IIf8bIWR1EOfZbyg3kFpeQ/b190gtryP75nukFlcBQlDd22kEaIDO9JS/fWoRk31uiDCATJwU3IUVlLc+IyxeQMVx4lX6vvF415CyKUCrE5WLTSbkLwVCGcwOAxZGpo+DF50yZW2OKylbxCyVlHpUv3SpZWqi6GGCl4R0lPV4qtzHmDFjnoZSKrGI20b5y3vU9rYgAv9OB5xhZWCpAEIIA/C3APxZALsA/ogQ8gdKqZ+vPe0fAfiVUqpGCPl3APxNAH+u/2fbfxoluWu2SDIKEZVaVZhl4CdBw/MtS9R1qqhlQ4ZBW90q72i/uxmul9v61xY9eDGJ4PK8KXjVsin9y7xwxwGhrCVQtidnQJLPXsYxhFdDcHGqNcumroZD4moF5W8fr3wnuYHsxtt7Z6MpY3Bm5lscBQhjutw5ZsyYgaHiCKWPv27YFYrAR1i6RO7NDyPpLDPIes1vAviklPoCAISQvwvgdwA0gjSl1P9+7fn/J4C/0NczHDIUoLMF7Xb9QzhMUJ/AiyoliMCHmc3f6nd4GywJViljkO2ERYHkeBelAggFd9MtgrtGrgDSJaPrQaOUgpJSTyHe4xqihoHM2utGZpO5qZ7KprSDcAOZjbeo7nzVGnuUwpmeg5HVNmVSxPCO9hGcXZk0B+cnyGy8BTNMVLY/N32HVByhuruF9OrGvf8OatlIr7+Gt7+jB1BSaaQWOiuijxkzpj+ExYtWP+nEgN2ZWxy5wbtBBmmLAHau/XsXwG/d8vy/CODv9fSMhpy6j2Z4cdp0nDkuCBm+6SsZRdqeKgmq/OODZApv6cE3dcI43KVV1PZ34MwvtX1ON6QCpIgT+RMCyjlSy+uo7m0hrmgvVCObhzu//Cz60WQUISxeIKoU9RTfxJS2+rpjEavLpiCV7tOZNkMIAXdcZF690QEmISDJAAmQyNVcC9D0QYXa3jZSy+tNdml14mq5bZ9bJyhjMDM58FcukgmeZ3FNjBkz6ogObS8i8PXmbByk3Zt271TbNAgh5C8A+BWAP93h8d8D8HsAsLKy0q3zGzooY3DnFwEoPf2pFHg6i9TS2tBNeEop4B3tt5Qlw/NTOFOzD56Ao4zByOSRe5OFkgrO/BK8g93G49xNwypMPXqXpBLpk9r+DqJqGcy04MwvgTkppJbXAKkAgsRQfvSbqmUUofzlfWNBi0pFBGfHyL3+fmQEkztNHXbKtArf67iZ0cH9w6+dbn3vlBCN8u19AuUxY8a0x8wVEJydtB7PT4yklMwgg7RdAMvX/r0EYP/mkwghfwbAfwDgTyul2o6QKaV+H8DvA8CvfvWrZy2NTbkBd2EF7twiFBLLmmHcwQuJuNaq7A8AsVcDs50H/ToZR/AOdhrSJPbMPHJvf4QIA1DTAiEUIvAg40iX3x5481RxhNKnX676GHwPtd0tZDbewjvcQ1i8BOUM9vQ8zHxh5GUJ4lqlZcep4hj+2QmcmfmRXMzqUN4+yOSOC1ACI5NHVG7uJ7Nn5wfW9C/qm4NysWGwbmTzw/m9HjNmyGG2AyNXaJLI4alMXwTTe8EgV4E/AvCaELIOYA/A7wL489efQAj5JwH8ZwB+Wyl13PorXiYjYX1BCZhlt5VmeKhciFI6c3hdO84/PoB/cojc2590cBaGYJYF4VWhLAdKqQdpmcW1aksfgzu/hMq3Tw1vURlJ1Pa3AQKtOD/C2Y7rjgvXEbWqFkzu8/lcR0oBSJWo9T88WCSMwp6eazY3JwTu4gqYYSK1vAr/zEV4cZZ4bM7ByOQGEpjWM5p1aRMZhajufkNq5RWsfH9058aMeU5QbiC1uAo5Mw+RJASoaY7sxnpgQZpSKiaE/CUAfx8AA/B3lFJ/Qgj5GwD+oVLqDwD8JwDSAP675Ia4rZT6lwZ1zmPuD2Uc7twSiuVSU5M2d9OgDxSCVXGM4Py0zQNK9xEphah8idrela6cWZiCO7d474xaS4mMUBDOm8zf6/jHhzCz+ZEpC7aDpzPA9SDm2vFBZdHq0hje8UFiOZWDPfnwyVHKuA68snkdiBkcVmGqkZmi3IAzPQd7QntqDrJVQIZBW+05//gARjrT1xuLklLLi4zw5mPMGACJCDNvUkcYVQaaT1dK/SGAP7xx7K9f+/8/0/eTGtM1qGki9+YHeCeHkGEIM1fQE54PvfEQAtwMHAgBs5zkxh4hKhWbHg4vTmFNTN77Bmykm6UTCCUddXXkzcmha+iJ1ghhuQQVhTByhb5PP94H7rgtk6vUtGAVJgd2k5ZRiOKHnxsN/HGtirB4huyrdw8OpPQinYbRYbjhsVm6biM76O0pIbo6qHzrOcQR4loN4cUpCDcaciWE0iv9RUKG7hoeM+Y2pIihhASgHuxKM0yMv3VjegahDMxiSC2sQCkJQtnjAgBKYE/OoFr7CgCwp2Zh5gqI/RoIZU3ODNcJLy9gpO7Xh0A4h7uwgtr+DgAFJYT+UlPaYnZv5gpABwkOGQR6ojW5+XpH+3DmFrWJ+xCVqCk3kF7dQOxVEZWL4G4aRjo7sKySlCKxnGp+r2UQIPZqMI0+iuX2EW47bWV19KRy768XGceoHew1TYwH5yfIbn4PJQVq+9sQvgfupHS52LKHIrgdM+Y2ZBShurfV0DLkbgqplVdjnbQxd6PVzbVsACgbqht3ryCUgjzF3EIIKCXhzC1CCQnCKEqffwEAZF696RhYUOv+X0jKOMzCJMxsHiIKkgCNIbO2ifK3T41AjTmuLqO2+dxkHKO6v90isuod7sHMTw5dHyE1DJhGHmY2P+hTAaTq6BghAg/A8wzSCONIr26gsv2lcY1xN903U3NtcdXcSkAoBaRA+fN71NN5ca2C0qdfkHv744v0rR0zOkghUDvcbRKbjmtVVL59Qma98/1iWBkHaU9ECgFAgd6hz6WUhPC1WbcMfIAQ2JOzsGdmRzYN2y9i30dtdwtmfgLO7AKK7/9x47HK7jdk197onrVr2QhCGaxc4UGvUx/IuN4zRxlD/u1PkFGog03GO3/JlWwRvq0jo2B8c7sFQil4Otd2oOFmKfo5QSiFkc4i//ZHyCgCYQyEsTvlRbq1ZsiotR/OyOYRXJyipd6qJMKLM1hTMyCU6pIsIS9iozkq1G3Q7itO/SyRomnIrI7wvZF05hkHaY9ECQERePCODwEpYU1Og6fSHRdPFQvU9ravsgVKwT89BLXMkZ8U7DX1m0BcqyKqNst6qDBE7WgPmVdv4R3t69KMm4I7v9QV9fd679K9dl9ET7S28/vsRyA+Ko3f9WwyQEAYBU2EaO3JaYTF86aMmpmffBa6dLehrzHz1r9TxhGicgl+ItJrT87AyGSffF21G+IhlLW1XQMAKWPIMEBUKSEqXoIYBpyZee0kMg7WBoZSujfXPz2GDHwY2TzM3CP6f4cUJQVkLBAWz6GEgJmf0KLabZIjz02DaxykPQKlFKJyUZcoEqJKCdbkDJy5haYLR0kJJWJE5RLM/ATc+SV4xweNPqrg9Fj3nzyTL1MvoIYJallQsWi76ETFC0AppJbXtHQEpXdmNntyntyAO7+M8pf3TceNLjgh3IaMIoTlou4tcxwt6jukgqgi8FHZ+tyYmjWyeaQWVxsuBtlXbxF7NYjAS3rkzBffsC6FgH96DP/4oHGsWvsKe2Ye9swc6BMsyghjsKdm4Z8eNY7F1QqcuQWExVafYKswhdretnZoSIiKF8hsvAMdkAPFGL0GFD/8SaNkHpWLCM5PkVnbHLnyXjuE7+sWl6Ra4h8fwF1YgVmYbNkcEMpg5got2TTdTzl6G4mXvfo9EhVHqF1Tu68TnB3DmZ7TgiLQwVxcq6D89crMGYQivbaRGEC316oa0ww1DGTX3yKqVcAsG8x2WqQx7KkZsCHIuDDHRfbND/CPDyDjGFZhMsl49OarJuMI5W8fG9m7qHgB/+QY2dffD115VUb6XK9r50WlS9QYg7uwAspY0ieXw3PtQXsUUjRrviX4J0ewJ6c7DrHcB8o47Jl5GLkCwsszUMOEmdcTvubkNMJryu329BwgRVOAVsc72AVb23zxAfUgkEK7u9wccBJeFSL0RzZIk3EEEQQAAWq7Wy3DNbWDHRi5fEuvr3bmWYaSojH1zxxXe/OO4Hsx/kY9kna9HACamsZVHKGy/bX54lJS+0/OzqO6/RXW5ExPsyzPBkohvBq8g12kV14huDxDVC6BGgac2UUw52EOBr2CMgbKHLhLq4BUPb9pCa/WUl5VIkZweqTNhIdoEk9J0VbcOLw8hzu3OHSDFcOCUqrlBqUf0P1HT6WTXIk7twhneg4yDEAIRVSrQPgdhjtCPylhj+k7SrbVcwQA4Xn3nnAfJmQUobLzFXGlhMyrt+3/PqWn8Nu1mFHDQGppPZFRGktwvDwIaZvNAaVNY/NKyra9HTLwQbkJa2oGZr4wlGWpx6A1wmLEXhUqjrUwKuNd6VWRUdjIJpS+fIBVmNC9MJYN7qaG7j2klOEpA633JergHBB7NT1F3I+TGNNTCKGghtmyMaSm2dGLtBtQxgHGAaX0sA4hyL562/a5Rjo7kqWk5wChDDyVbtsLy1OpAZzR04m9KuJKCYDOqFHTggxbN3i33VueS1Z3vII/AsoNpJbWgBsLZGphpTkrRqnWQLoBoXqC0JldHNnovh0yDFH8+CeofPuE6u43FH/5Y90ILtoLdj6E6+PUUBLB+Smqu9/gHe21SF68JDqJtfJUuqc38MdAKANtYwlmFiafVLJ77hDOkVp51byWEIrU8iuQPtyICONw5pcApRCWi7rseeP8nA6yNM8NKQVkFCL2PYgwhIw7C1vf+nviWGeBugChFPbUXEtfs5HNj+zQzfX1Pjg7gTO70PIce2q2VeT8GfI8Qs0BwGwHubc/Iipf6mmTXAGE86byEqEM1uQ0gtNm21F7Zg6UG0NVinoqUsSo7W9D3Vi0anvbMDO5J5eyaAcRQmqYbQPhl4BSSmcSU2nE1SvpD2IYsCenh+76ooaBzPprVLa/QCQZQDM3AXf2ZdzgHwshBNxxkX/3E6LkczZSaRDG+5JBppzDmpiCmStA+B6YZcMqTCIql0BMA4abfhGDTzKOERYvtH9vUma2JmfgzM7fe7Ndn9INzk9ACIU9Mwdmu0/O+jDTRO719wjLRQjfg5nNg9l2z5IAddeVXg1oMfvKzimulsEdF5n1NwguTqGkhDUxpS0GX0Cr0PP/C3sEoRTMNMEmZzo+hzIGZ2Ye3EnBPzsGAYE9PQue6o4/oowjyDBEXKuCOQ6YaQ+uMVLKFnkMAIBSEGH45B2dkZROm03QCZzpp023jSpS6AZu73BPi/wWYsS1CpjtwswVhrZBlpkWMmubDbkQSllflPVHnbpMx6BM1+ulz+uK7cwejj7QfqHiCLW9raZjwdkxjHRGu5DcgRQxvKN9BNeGMaJKCamlNZiFiSdnvqlhwJ6YetLvuAsZ63XGPz0ClB7Y4qlM10uLZi4P73i/sen3T48QlovIvHqjM/Id1oy6LZ9eXxL5pBEve4722Y8AlBuNCT+ge/53Mo5Q3d1qSgszN4XM6qBGrgmYYUK0UY3vxt9MuIHs6+/gHe4hqpbBTBvu/FLHDNtzR4YBKt8+AQBqB7uwClNgqYw25R7SAK3Ocyrxj3k5BG0kSQAgOD8FT2fvzgYL2RSg1akd7sLIZEGGvDSppERwcQrvmrJBpVrWUjDTc13NhhNuILv5PfzTQ8TVKpjjwqlXoDpkj5WUiL0aKlufGsGdkSsgtbAy9GvibYyDtD7R7RuT8LzmPi0AolZFWC4OxCSbGgac+aVG4FCHp7NdmV4lhICZFtzFVT1q/oINn5WU8E+0rpW7sAxqmAguzgDo7C0hevdYH+RQSoEQosvxL7Q0PGbMU+kUhBBKgXt8rTpNv95sERlWlIjhHx20HPdPDrUUTDeDNELATBPu3BKUFNr3+Y7qkxIxyl8/NEmRRMUL+JYNZ2Z+6No/7svLvMs9A8IbAVqdqHT5aHPmuvCuElJPqj4wVcxsB+m1Tfinx1AihpnNwyxMdTWYqls3PQallC6XEjLSvQwKCkoKmIVJKClR2frceCwqXcKZX4ZVmEBcrWgv0UhPR6UWV8FSqRdZHh4z5iYymb7XG5i7xZ+NbAE42ANuBFv2zPy9vlO6ZM1aBp102Xj4N09KqfZDWkolUhfdp+74ch9E4LdoxQFAeHEGe3JmHKSN6S+d+kG0qvLDv/Aq6Smrbn9pTB2Z+QmdqblHFlDGMaq73yCjCFZ+AoQyRNUygsv3yL56N/B0s4wjhBdnCC7PQRiDM7MA5jgjGaxRyvTOFQTlrU8tj3tHezCz+abgTYYByl8/IPf2R8AaB2ljXjYyCuGfnSAqXYJwQ5fSLPtWQWzKObIbb1Hd24LwaqCmCXd+pa21VjsI40gtrzV9L/WU7trA18f7QAgFNU3IsFkKhgzLEFynnr5H3A+HidG7Q40BAJjZHLwjo0mHTU+TzjyqAVXFsS5VXhPHDC/PwRwX9tTs3WUyKRFX9OCAd7Tf/LufaGqrpISMY0SlCygpGzZa9+2BkHGE6s63hhUXAJQr75Fe3YCRzY9kCZA5rtbNareDTTKi7QguzrRw7JgxLxQZhahsfUbc0Bj0UK6UkF573fCRbQehFNxNIbP+urFOPsR+jVAKns4i9+4nROUiCKG6F21ENoqEc6SW11H+8uHafYJoO74h6DNlpgXCjRZtUntqtkWqRsYRVCwg4wjMsoBbhhEGzWhcHWNaoIaJ7OZ3SWNlBcx24MwugBr3/0hlfQoGBEpEIIy19EeEF2ew8pMgd+30CLQURjsF9CcGQbFX036Yye/2DveQWnkFM5u/1w5OCdEUoNWpHe4h66bv/tuGEMoN3WvWZlEiyWPt6FVZYszLQcZxUvIbzT5HPaHYKgLtHe2D2a+aJljb8ZT+4nq7xm2qAMOKloJJIffuNyACDzIM9aDSkPgEk3qmc+cb4loFhDLY07N6U3/t/GQUobL95Zq9GYG7uAIzXxjKysrwndGYe3O9sRKUPqjX6KbRNU9nkVndRPnbx2aRRXK/plhQBrMwifD8tOkwf6ISuYwiVHe/ASCwJqdhZvMAIYiqZUgRg9G7Sw2yQ1apnYL1KFEXVa58+9h0PLW02lHk0erxiP6Y54tSCjIIUN3bQlwtg5oW3Pkl8HRmKG9unehk6SejAHi6y9azRcYxZBggOD8BGIc9MdWiDTpICCFglo302majb5DcyIwqpSdUm/1nFWp7W1qBYQiv4+E7ozEP4iGNlXW00fUnyGtyGXGlBI/pcql/fDXBUx97vgvKGNy5RRBCEZyfAlAwcwW488tPGhxQSkGGITJrmwhLFygnJVkzl2+ftWtBpSurAAAgAElEQVQDqwve3ni+kc6MdL8CIQQ8lUbu7U8Ii+cAtDgs4drKx5lb1KVnpQBK9WcxglnDbiJFDCiAMDYUu/9RQsURSp9/3djEyTBAZeszMhtvQUfIH7JTP6+Rzr4IBft21CfBAdUS2ABalzE4O4F3tNc4FpwcIfPqDeIkO88d50Hl315x2/1GCYHw8rztY3G1fGcWdRCMg7QXiJKyKUCrExUv4Gy8g398AMI47Nl58AcsvpQbcOYX4cwktjFdqPMTAtjTMwiL50nwpwmLF5BxjPTqq7uDSMaQWlxNMnLJ72Uc7sJKXzMAKpmCIpR2bSGrl0+cmfmWx6zJGVjJBCihtO3i+1KQIoYMfHhHB9ohpDAJM5cfa7Y9gKhaaWtl5B8dgK+6IyNKTCiDM7/UpPdFDRPO7ALYC9zEyDhGVCnCPz5MvhsTsKdmm78bUsA73r/xkzoDZU/Pobr7DYRxZDffgbWxfhsaEimitg8N6VowDtLGXEEIiGEg/91vACA62/DAm7o2Fu+mqCGHmZ9E6ePPLY/F1fK9eqwoZTByBeTSGcSVMgjn4E6qL76HwJUKtn9+CuFVYaSzMHMTPc9qPUWuZFioZ76eKuMS16qofP147d8VROUiUktrfdXbkyKGjCKEl+egnMPIFkCHqGR0G52GUZQUUEqCYDSuNco5rMIkzGweUaUMahjammmEA7S6g8dDN39KKW11dc1JwT8+RFyrIr2y0fhuSCHaVi5E4DcExZWIUd3bRnrl1dBqWFLG4cwuoFx533SccAP8mhXVMDGc7+SYnkIoBXNcCK/WdNzMT4AwPlRTLiSx9uhY2rxnybPRsDvR/3S2iiMUP/7cGMqISkX4ZyfIvno70jeGXiJFDOF7encvBayJaRiZ7KMyXzKK4O3vtByPStp3F326oUghEFycNZ/LwR6ym2/BnVRfzuEpGOlc2+NmYWpkJhTrUG4A3OhK1kdJCRXHiLyqnuC03Z4NVCgptWdvskbLOEJUKSMqXYLZjhYyf0DJUcVRyzQ+AMSVcjKVrz9X3e9McLNpj1p2U49fXCnde00eFMxykF57De9wFzIMwdNZuAtLQ7sWj9Y3a0xXoIaB9OomqjtfGw2UZn4C7tzSUAVodQhlMDJZROVS03FqWk8aSugHSin456ctU7My8BFVywPzYhxmlFKIyiVUt780jsXVCszClF5MHxEQiA5DIlJEYOhT4C5FU4kNAKAkqrvbyKxvDn3pVUswrKG6u9W4ERu5AszcaMrY1JFCAASPEnmu60tely8ijCO78Q7M7l7ZT5frA/gnh1BKwZ6cAbVtVLe/IK5WGs/zTw6Rff39g3qrbk6HN45fL20zBntmrqlfGQDcuUX4J4eNfz/Vo7kfUM5hZnPgrtvo1x3mwZfhPbMxPYWZJtKrG7pfiWCoL1TKOVKLayh/+9iYRqWGiczaZt9Klo9FSQnRZtwf0IHHOEhrRcUxvIPWzFd4cQpndgEPrqoRAp7K6F3+jeO3iZd2Gy1d0aZk5FVHYqqQsnrbQBYqjpN2CNb10pYUMZQQkFEEahggjPVkbZJxhLhWRXB2AkIp7Jk5UNN60GspEevNxLXPVYkY1d2vSK91J/BWSiEqFVHd+do4JrwqUktrTQGafm0B//gQ7sLy/UrolLbdAOOG2wxlDPbULIxMTr9frD7Nf9IkZ+LMLw39mlxn2DdFdUbj3XxGSBFrAdIHNNVLKQAhIIXQuz3WnYBqWPsG2kFNE5lXbxq7O0LZSGg0kcYi2KrTZmSyAzij3iKF0DY7yQ1CCqFLQZUSCGcw3PQ9yjEKMuqwu29nS3MHOshfQenTr5uyA+7Cclf7J++iU0mQWsM3UdaJRs9pj4JbmZTfrhuR21Oz2nqpi+uVFDH840P4p0eNY2HxAunVTRjZ3P3LhUK2HaaIa9Wulf1UHKF2Y9NCTaut1hsAxF418bu8O0ijjMNdXEX58/ursiUhSK9utAyCUM5BeVpnoECgRKxdGmwHhDHYM/O613fI1+RRY3Tu0iOOkhIiDFDb34HwPXDH1ZZLpnmrQ4AUMcLLC9T2txtf+l4sWqNAvY9klCCEwMxNwD87hgyuSm7cTQ20D6k+cNGthnUZxxBeFX49KzE9B2IYiEvFG1O1DNnN727vBSIEzEnpDNN1KH10OZ6aFnJvftATinGsld55b/svZRxBRhGUiPXfS7XW3/UABICeMh7Sfph+I3yv5f3xT49g5PKgvIsyH0I2BWh1avvbyLrf3V/gupM7AePolh+nUq0m7CIMYHeQEuFu6kFtIMy0kN38DiIMoKQAt51bJ8Hr9yvCDdhTs7Dyk9oP+YXdj/rF+F3tEzKO9IRiEmhF5SKKH8vIvfkR7BbvNxlFTZM3gF60eDqjhV3HDD3UMJB99Q5Rtax7q/IFUMMCoCDjuG+LmxQxlFRQUQT/VPeR2FOzoNbDSjytv1fAPz2Ef3zVmxJeniO1utGiSaSEQHVvq2ly7CZapHcVpc+/NNlepRZXH92gTggBMcy+lZe1FuHHq+EcQpBaXoc9M99UMrKn5xrTccNEw41EqaastRQCSggIrwrCOZhpdy3AVFI2yexcJzg/BXfTXcvSyA4ZWZ1Nun8GjFAKI1dAVLxoOm7PzndNkoQQAmpaTeLbKoqgFMCTifXGcxmHPT1/5+ZLCqGz0tfkeYxU+lHnNoqOLaPEOEjrA0op+KfHrelvKRFenrXVuKrTSXgvOD8FT2WGstF/TCvUMGDlJ2BkcokcxAeIMAB300gtroBads/KBDKOEVfL8M+OQQiFWZgEd1KoHezoYGppTU/2PjKrpqSAf9yalfD2d+AuLCO60QsWVyp3loKYbSP/9kdElTKUEDAyua6pmz9WruAhv987PmienlYK1e2vyH/3E8xsHjyVaSoLDxM3vS2pYWq/Sm4gLjf3RlHDRGbj3a0bzXtzyw2fGmZXPy/KWFuBa2Y7D7Kxq5fSAzel3VYogzM9mzitdOezJZwjtbSG8tcPN85XIb38CnGtgrA+3ZmfuFPvS8YR/NMj+CdHjcb51OIqjGx+fD8ZQsZBWj9QCqqTFUnY/nidTruxbgqijukfMgxQ+fqh8e+4Wkbp0y/Ivf0BpAd9PlII+CeHTRNYUbkIZ34JZq6gNZIOdnT57w6LLRnHutm6oi2BuJNoS0mJdtkHGYVtM1/0Hjd0QqjOfBUm7/4j74mMI8SeB8pZ43un9fJYV6eElRCIShftHkHseTANc2hvhlLEqO7tNPU7yShE+etHZDbeNpWu6495h7twF1e7IFxNYE9MI7i5oSWk+3ZmjMFdWGmuUhCS6OY9LDNEm8p+3W9IJ4SAuynk3v6I8PICSskkGOOgjMPMFWBk7z9hG9dqTVlvSInqzlfk3v448rqKz5FxkNYHCKUw8xMIi60Lt1m4vfxi5grwDvdadnz29NxQ7sLHdEYKAe/GCDugM1FhuQS7B76aSoq2vTf+8SFSy+sIixdQQnQ0ZK8j4xj+yYHefSdQ00R2452+Dglt+OXVYZYNpVrFht0BTIDVG9LN3ATKXz5eCbMSgsz6a/BU+tbe0IdCuAG0GX4Y+r4dKdsGmDIKG+XPm0TlIiBFV27w1NDXVG1/G7GX9O4urnT9faOU6eAmlUZQvEgErx/vQNHrsh+hFMy0rtxc2rz+fdD2TsdtHwuL53BmFh59jmN6w5CvGM8HnkrDyBWghAB3HD29xtidYoqUa82d6u43CN8DNU3daNyN8sKYB1F3Dog9D0rE+sb+IPFf1Vm1vYNW0ZPpcGNVIm4E+Xra8vYARYm4KUADdBbYOzmEM7sId2G5JSvhLq2BWTbcxRUEF2eglMGenQez3b5ngWUUgdkuage7zZ+BUqhsf0Hu9Q8gRneCNGoYcGbmUdn63HzcskZCRwqUNvUC1un0mVFu6O+GUk/+XAml4G4qMclWAKE9C2wp5wDncDs04D9bOg4EvJwsmu65VLqyzdijNPL6xThI6xOUG0gtLCMsXSIqFUFtG/bkzJ2N0IQycDeFzPob6JISGQnpiVFGykQ2olwCs2wdECdxTnX3a5M2UWppDUaucK9AjTIOqzDV1Ohbx8wWunb+19FNwaxFJoBaNmQSGKaWVu/MbHUa94/KJTjT81dZicvzRuaYcgOEUlgT0zBzBX3DHVA5Rfg+mGW3ToxCT85paY/uZUJ4KoP06ga8o33IKIKRzcGdXRz6KU7COKyJaQQ3sq/McQGiA6ib14I9PYfa/g6c2Xktx9CFjOSoaFiNGpTpnrmbgw4gBEbu+Q+iKaUgw0ALudeqAKGwp2ZgT88O7TU3DtL6hJ72+nTVTFwuIjw7RfbN/dShh31xHxZkkiV57LSikhJxpYLKt09Ir20ivDxDcHEGKJVkhVbhHe4hrulArbq3hXwme+9Sj5HJ6tJ3fSCEEC0AafTmq0gYR2ppHZWtT9cOEqQWViDCALm3P97LRqbTBCIzrUYgCM7hzi22ngMhAzcvZo4DFYVtA1YA9w4slJRQIoaCvsY6tRxQrnuFuJuGNh+9vy7iICGUNkpqwdkJoCSMbF4Ptxgm0qub8M+OEF5eaA/MyRnIKERUukRcLSP3pje9lc8RKQQghRYUTyYs+9HCQi0bqeV1nVWOI1DLhju/pNseknMZNPX3ptsi6yqOUP7y4UoTTkn4J4fJpPVsV1seusU4SHskMkpG1AnupbotAq/FK1NJAe/4EKn7qkOP6UhjgvFU91vY07PgbvrBpRIlYlR3vsLM5RHXKk2SACLwUdn6jPTqK5S/JM3/SkFE4b3LWJQbcBdW4MwtQsYRGDd1ur1HN3BCKXg6g9y7nxCVLgFCYWRyoJw9SEyXGiaY7TQcH5LfDmdusWtSA72EcgNBpQRrcqbF2sbMTwDs7u+fjCOExXNQboJwA4rEunnb6BzkjuLminID7twinOnZ5MDV9UkNA/bkrO43jAX80+NGdvLKJWAcpN2FjGMEZ8e6R1UpEMaQWloDT2d7GswrKaGkBHNTyGy8BaSA8P1kGtlD/t2Pdw4Q9RKlJGQYora/g9irgdsOnIXlxmbwqWjtwtZhveDsRPueDuG1Ow7SHkg9XVr+9gky8AEARjqL1PL6rQuy8Lz2x/3avdWhx7RHSt0Me90ouFItw5ld1LujB7y39UyJkc3rgY2bjyeWNYTzhsDkQ3d6OnDkD/LXewoNc/mp2Qf/rFIKMvBR2duCu7iKqHSJqFICNUy4c4sgI9IbSTmHlZ+AigWoYSI4P4GSEtbEFKzC5J2foZ6SPYKZzaO6t3VlT2ZaSK9tgt/oa6r3Lwrfh1IS3HH7linpBoTSW2/WtYO99n2U4zaMeyG8atN6pYRAZetzTycspRCIKyVUd7/pbDKhusxnGA3rumjAVnUyilH8+HOjJzKqRIg+/ozc2x+7sl4q2X5ASil55/DUoBiNFWOIUHGM8tePjQANAKJKCbWDHZ2i7QBPtVeXN1LpoTcJH3qEzkjexDs5aJQ/7w2l+kZz571GP8FIZx8tsDoK1K93Ua2g/OU9ZBjAzE/AzBVADHOoG25vQrkBZtuwJqaQWXuN7Ku3Wsz3PqVYKUC5gdrhXlM2UYYBKlufW2ysZBCg+OFnlL9+QOXbJ1z+8seIa5WG08MoQxiDPTXTcpya1tD29QwTWvy504RlO+mW7qDiCJWtz1flfiXhHx/o4af6ANuAY+zw8rx1aCXRGX1qECXjSLdetAmCtSvMSdss26AZB2kPREnRpPxcJyxe6Bp6B6hpwcjmmo8ZWl9nVHbXw4pSqkX+AUDHycbbIFQbCUelIsw2Gl2EcVDDBOUczvwSUivrfZNVUFJCRmGj4b8vrynia/0bCmHxAt7BrtbLGtGAgxACahi3lilvopQCc13E1dahDxn4TcGXjCNUdr+2TpFufek43TtK1IdB7Jn5xqQgT2eQefVmJMu7A6HDdfeQnigpBGQct5W5aUdYbC+MHl6ew8zmdCuE+3DXgW7S7t4KJE4QTwzSlJSoHe5qt5NrZU0jm4eZKyA4PYJ3fDh0G6nnmwIYMrTVzRqE7yEsFcFsB2YmN17UukBdo0jdyGZolfKHBcA0aSCNKmVQw4SMQoQX5wCULm2tboAY2uydsP5N2coohHd8gKhUBDF0zxCz3d4HiJ3+PkLwEPucUUdvpEhblXr9hGvvk1KN8tF1lIiH7gbwWCjncGbmYU9O6wM9lMp4bjTWmNJl8wP3nLBUUvf+eccHkEEAI5uDVZi6x72kw1pICEAZMhtvBl4VMAsTCM5PWo5bT3BEaaAU4koZPuNIr23qNiMQRFU9KAalEJWLUDN322r1k/G36oEQyto0UANWYerOXgLKDdC0ASN9/4btMXdDuIH08jrKXz9e3UATr8THiKZSri2cZBzDmVuCM7cISAVC6UCCahlFKH35cFVij0KUv3xAZv0N6AOa/x8DoUzLdVwr7wOANTE18AW9n1BuQAmpJ3MvzpoeM9pYAHWaIsUQTo89lrv61sZ0hllOY1JciRjUNJFaWr9XuViGoe7bSta6uFZBeHmu14Nb1icznwij39hc2VMzYKY9FNJOzLJhTkxpi60EI1cAf4Sv6E0IZaCmhbhaabQp3IQaxtD1Vb6cVbZLUMNAem0T1Z1vuvRBCMz8BJzZhZHqz3lOaNuUNHJvf2r4RBrpLOgTF51hyQzIKGwJkgDAO9oDc3qbTaOGgcz6a60rVK3o670wCaeHu03ddB8DUAAhQ9PnRE1TT7NSiuD8DICCmSvAnV9u+gwI47Bn5uEd7Db9/FP8UUcFGUeJCO3wfG7DCOUcVmESZjaXiADTewVJUgjUjvZbsrnC9yAC/9YgjXCOzKvXqO58a1i2ufOLYJYzNGudnixegjM9BxFobUPCWFeuJcI5MmuvUf72ASBE6ybeWFeducWheS/qDNfZjAgsKXspJXWf5YhoIA0zMooa/VbMdvUX8wHvqbZNMcF6YK00aDo1s8ooat+L96TXivR1TUhjGlFf75taQ4mgp9e7FDHiShm1/R3IKARzXKQWV7VI6oADHEIImGHCmV+CMzOvD7Z5LwilemKUG/BPDqGUglWYgjUxOXQ3gG6hpITwPVT3tiH8GpitM0V8CD63YeVRmUgl227YAC0RZKQzHX+UUgaSyiC7+e4qMGSs7edTn3IHSMfn9Iq6E8RdbjwPhRACalnIbnwHJSXS62/gnx4hKl2CGnoDxobQfeJ5rhh94LGLrYwiiMDX9lCuO/SWFP1AJuW767sad2kVZm5iHPwiUXtvg5HNd63kqJSCCHxUt7/oUj6lsKdmk+lH3rfgQgbNZQjh1VD6/D4ZwR+O0hqlDLjjO0u5ATM/0Wht6FcpSUYRpIi0fi7nAOOAENpRgVBdsu/BZynjCKXPvzQyPMKrofz5F+Te/HCvm63OwOn/H/fpdoZQBiOdbWm3AXCvkqDu3739eyTjCP7JkdaIJAT25DSsyelnkRm96bHqzi1CTc8OdU/lcJ7VM0WEAcqf31/LjBCkV1/ByORe7G5TSm06fjPtXNvdgpHOPVgzSEshjI7C+30gjMNdXG3yxmS2A2dmrmvXjYojlD//ctVHJfV4PjVNWIWp/gQYQsA/aZVSgdKm32xqtmdK5L2g16bbNxFhoNXUkwk55qaRWlpFZesTZKCP3UfT8TEEZ6etAxVKwT87gTu/1PH6UVLqzcHeFkStqjNwCyu6jP9Mvr/dhFCtbRaWLiDDqwy7OTHVlSBKihjVve0m2yjvaB9SxHBmF5/dZzIKfZXDvco9I6QQqO1v3yhdKVS2vw5c5XmgCNk65VR/yK/dO3si4xixV4V3uAcZhjAyWThzS0OTfXkKlDGdlcnkIPyaHkAxza7ubIXvt210D06PYWbzfbN16jj9SAhEGGhLrmoFzLLhzC/pnpUXusG5joy1U8Z1CQNnZg6Vrx+b1pyoUkLtcBfuwkrXbrhKqY6yMCqOoeK4Y7Aq4xilT7++ysD5Hspf3iP35geADV/paRighonsxneIvWpS4sxqSZluZIKEbPX1hFbkd6bneia0O6Yz49WtX0iJqFxqPa5kixDmi4IAhLcPpB4ShAjfQ+XrRwivBiVihJfnKH/+5dm8t5QxMNOEmc2Du6mulx5UBzkNrUHXH6kNyhisDj2FRiaH0sdfI7w8116RlRJKn349lOKTA0FJPdhxDUJZ2/enrWDoEyCEdPzczGwO1d1vHb+H4eV52+vLOz16NnIlT0VGEcLSJfyzY4jAhxQxqGHAzObhTM+BO27X1oOOgrFKDa0i/3NnHKT1kU4lhlHwPuwVlBtw5hZajjPLBn1AFs07arVwklEIEXiNPkDh+0lj/HixkUJARiHiWhUiDMAspyFMeh1rYqqv5ug8lYZV194CAEKRWt1AVCm1CsEqBe9k+MQnB8ZNeY9OFeoelK6ZZcOenms6Zk1OQ0mptac6iPhKEcOamIK7uKIn5JN+KRXHHTcOLwkRhih9+jUq3z6htreN4vt/jODsGDLujSgyoRS0jf0Sc1JjZ5wBMS539gnCOZzZRVR3vjYd56nMiw7SAIC7aaTX38A72oOKIhjZPJyZufvvDpXquGjJKIJ/etwoqVLDRGb9NahlD1wTaFDIOEZwcQrv4EozyZ5fQmb9DarbXxrZF7OgfS37+T5RbiSeq/NQUjR8R/02tl8AoMIwmbJ+4ftNxmBNTiM4PWocUlHUVmbAmpju+ppDOYc1OQ0zl09M1g1E5RKqu7qPstPGyJ6chn98CP/0GMy0kFpaQ3B5poeGXnhQIIWAd7TXkg31Dvdh5ifRi9s34Rzp1Q2Uv3xoBNbUMJDuo7PKmGbG73qfIITAyOSQXt2Ad3wAJQTM/ATsqZlnMTXzFChjMDNZcMcBlHqwETVhDGauAP/4oOUxZtuIdouNf8soRHnrE7Kv3vW1qXuYkHHUouHlH+yCr79BdvM7PQlIk0nAATTnt7sZmNl828/XyE+Md/jQE6fOzBwoY/DPjgGpEAc+0uuvmzQdrcJUVwdOrkMYh3e0j6h4qa+hxnHW9jOVUZT4weogRAY+onIJ2c23bbM5LT9fnwglV60RUsS6lDsiOm1SimT6Vuom9utrn5SIK602ZICenu2G4fhNCCFgtoPcm+8hhdAbNEL6mk0f08w4SOsjlHOYdfVkha7qz0ghoBKNKcI5uJMaCgXph/DYRZVQCntyBlG5BOFd2fG4iyva0unGLl4GQXITeZkLT3jZ3sMvOD0CX3kFNoTBKzVNWJMzCM6ujKl5OgMzkxupa7yXUG7Anp6DNaHLxfX1pV+ajpQxuHOLKAd+wxaLMI7M+mZb54/YqzVNKGoUvONDpJbXO76OlALC81Db39bBipNCamkVhDHU9ncRV8uglgV3fklbpw1ppaKR0T7c13qHlMKdX4aZL+jNESGgptm2r/A+QexjIYRAEYLw8gzB+ZnuOZycSXT+hm9teO6Mg7QB0O0LXQqBqHihTa8TCOfIbrzruiDgsKKV8Te1TlQcg1s2FIDi/h+3/4FnZM/zUDqVLfrpRfpQdBl0AfbUDGLfAzOtZKJtfNO4DkkyoNdp93lrMdPuf9bUMJFZ1b6ISilQxpLNYuv3rbOZdl2kuX1wpaII5c/vUS/VC68KJQXKXz8kThWAqMUof36P7OvvQTvoDA4aGfrNGW0pUdvb0oNBjtYmdOaXUP70S9PPsR4MDjWdl4hR299pbOYUAO9wFzKO4MyNnXX6za13KkJIlhCy0eb4b/TulMY8GClQvaahBejG29r+jk7/vxAoN8AdF2YmC2qaugxaaJ064228Fl8SRrbQdkjA7lEZrFvQRIXcyhW6OtH2kqj3aFZ3viK4OO3J9DM1DDDLBrcdUMNsG6ABOhPaDjOb61jCVkrBPz3Gdf9J7aXsNwK062iNrzYeqgNGSQn/tNVIHIAWkU1gloPs6+9hZPNgjgtnbhGZ1c2eCv4qIdtm24Ozk/Z+tGN6SscVmRDyrwH4BcD/QAj5E0LIP3Xt4f+qGy9OCPltQsh7QsgnQshfbfO4RQj5b5PH/y9CyFo3Xve5IcKw7Rh7VCk/edReKXVl2TRiAZ8uvyzAmprRQUniO5leftlNsDTJsnI3DUD3oGhz5tHXlBvTGRnpScHa/jbCy3NUd76h/PXDwGRqdHl2tukYsx092NBps6BUy6QoYQyqo05b963TugIBCO2Qybz2t1PGwB0XqeU1ZNbfwJ6e670jQ6f3S8mb3uxj+sBtd6q/BuBPKaUOCCG/CeC/IYT8NaXU/4jOw933hhDCAPwtAH8WwC6APyKE/IFS6udrT/uLAC6UUpuEkN8F8B8D+HNPfe3nRqeAQ0tYPP6jkiJGVC5dCcSmM3AXV0BNq69lMRlFEFEACAlm2w8aLLhu2KsPPB8ngseihIB3uAszX4AzuwAZhQguTuHazlis8pmilEJwcdbS3yR8D3GtAjNX6Ps5Uc5hT8/DmphGXKuCmlajjN0JQimsiammTI/wPDizi22fb+Ynumad1k0IobCmZpuyZnXsNppz/RzgIZSBGq29cFqGY3gz7U9FRhGiaglRuQQjlYGRyQ2FRdltnzxXSh0AgFLq/yaE/PMA/mdCyBK6E0//JoBPSqkvAEAI+bsAfgfA9SDtdwD8h8n///cA/lNCCFFjoasmCOMw0jlElWLTcXd+6UkXmahVUd3+0vh3VCmh9PkX5F5/f6f/W7dosdIiBOm11zBS6XsvGKNg/dFPwtIlonKpRVzZyOZg5Sfb/oxSKiknPS/LrZeCkq1it3WiSnkgQRrwODNtZjuwp2bhJ3IjSurpSGduEd7hlV4iT2V0kDasfZaGifTqBqr721BRBGqYcJdWBz5JSThHem0T5S/vG+VNwp+3DIeMQpS/fmx4ooYXZ6CWjeyrtwMP1G57x0uEkA2l1GcASDJq/xyA/wnAD1147UUAO9f+vQvgtzo9RykVE0KKACYBNG0/COjNMKEAACAASURBVCG/B+D3AGBlZaULpzZaUM6RWllDeHGG4PIchDE4Mwsdjbnvg4xjeG0kD1QcI/Y8mH0I0qSIUdvbat7RKYXq1mfk3v4wDrwegZIScaWN8wWAqFyCmWu9qck4RlQpwjs6gIq1jp07tziQ8qj27pSJd+c4ULwvhFLwVBpRudjymNGhN2xYodyAPbsAa2oWKo5AuAHCKHgqBTM/ARH4oIYJyvnQ9i3WPWiZm0Ju8/vGIMegJvKVlFAiRlSrAkqBu2lk3/wAGYYghOjewmcaoCmltDLADdN6GfgIixewp2YGdGaa2971fw83amVKqTIh5LcB/PtdeO12V+LNDNl9ngOl1O8D+H0A+NWvfvUis2yUG7CmZmEWJvXo9lPT40p1bBLtpB7edTpYaSkpION43EP1COo367CNPx930y03CKUUokoJ1e0rEebw4gyiVkWmj7tMpSRkGMI72kfs1cDdVEOhflgzJcMEIQRWYRLB2UnTpofZTtKbOFrURY5x05WE8Z7oh3UTGUWoHe4ivDwHoQz21AysyemBBpTC91D68v6qh5kQZNbfgKda14TnhhICUbW9Hl1cLUNNTA20zHvbK//XAP5lQkjjbk8ImQXwXwL4F7vw2rsAlq/9ewnAfqfnJOeRA9Be5GmM3vFwoyv9C4TzRNW6FZ7q16JOOu7eXrpLw1Mwc4WWAJeaFsxsvuW5Ko7hH938WkJ7CHZo1u4FMopR/Piz9u4MfIQXZyh9/Lltw7iMIsS1KsLiBUQYjNzAS6+ghons5ndwF1Zg5ieQWl5PBkb6FxzIOEJUKcE7OURUrfT1GhoGZByhsvUZ4cVZYwjCO9qHf3o8MHszGUWo7HxpHjJTCpWdLx0HMp4TSklwu33VibnpntioPYTb7uZ/CsB/BOAfEUL+MoCfAPwVAH8TwL/Rhdf+IwCvCSHrAPYA/C6AP3/jOX8A4N8E8H8A+FcA/INxP1p/qO+842r5qkRCKFLLa31rxCVcl21r+9tNx3k686wbWHuNvlm/Q3B5jrhagZHOaBuetjdr1THI6VdGVSmF4PykZVJZCYHg8vxqKASJiv3XD02lC3dhGWZhciDuCcMGNQzYUzNQarrvGRIZRShvfWoI3QJaDie9vD7wvp9+oaREXGvtDQxOj2FPzgxkXVNKQgatmnUqil6ELy5Boj1nWU3vAzVMmLnCwDOJHVctpdQFgH87CdD+V+gs1z+tlNrt9DMPIekx+0sA/j60auHfUUr9CSHkbwD4h0qpPwDwX0BPlX6CzqD9bjdee8z9oIaB1PIalND9CtQwHmzZ9BQIocl0FoV/fAglBcz8JOyp2aHtNXkK9eZ8bRFDeqsOb5iwp2ahJqdBCO28EDEGI1tAeH5D04mQ/gklKwV5w3+yjvCvjmvtqaOW3pLa/g6MbB4YB2kNWsrayc24l9/tsFxsCtAAIK6UEHs1mEauZ687VHQIerQDymDyD4QQLftx89zqx585hHHIsIzU0jrialm7WNgOjFxhKCo2HVctQkgeWvLitwD8NoB/AcDfI4T8ZaXUP+jGiyul/hDAH9449tev/b8P4F/txmuNeRyUG8lVMpg+D5qUXY10DsDDfT1HBSUFYs+7MjgnBPbUrNZF6lHDLiEEWgmnM5QyuLPzEF4VwqvVfxDplY3+ZVSpDtbb9dFZ+aupRCUEwtJl298R16oD6VWqN2SHpaLeZGTzIJwPTVZPxro0HFycgTIOe3oWxDC6riqvpETU4bOJSpcwsy8jSCOMgXCjpYxoZHIDC4gI43Cm5+DdaGuwJqcH5osr4whKCMg4AjUs7f/6xIBJxjozqKQEZbxhm0YohZHJQQQepBRgbhrcdZPWoSEO0gD8PwD+NoB/VykVA/hfCCH/BIC/TQjZUkr96305wyFEJQa+g06DvhQIIc/eDF0JgfKX91eixErBPznU4p6F9r2B/YIaJjLrryHjGErEYKbV92CZp9ItMjN1FfYGSU9mu6zboDKvIvBR+vRLQyDUO9hFamkVRn5i4PY6Mo5RO9hDeHE1LB+cnyKz+Ra028MEiXF3u0DtKVPoowbh2r6u/OVjo12A2Q7cxdWBBe6EUliTM6Cm1XBzsCZnYGZzAwlSZByhuvsNUenqu+4sLMN6QsuCjCJUd74iSibbCWNIr26AuymtC8c5KM+A2S4ANTSbKOD2IO2fvVnaVEr9vwD+GULIv9Xb0xpOZBxBeB6Ci1MQbsCenNbTZfe4WTVU+6MIzHFAGB+KKH3McBBVK21dI/zTYy2qOODxd8oH65NJuYHUypoWNvY9MNtp8e6knMOZW0T5c7PXITWtgXjY1m82NxXcq3s7yGdyQJ+DNJ1FEI3pbyVFU4CWPAu1vR1k1je7+nkTQmBNTCM4O26aGifceDFZNEC/D8x2kHvzPWQc6w0o4wPvyaOcwypM6oxevWIxCCkQpRAWL5sCNADw9ndgZnKPallQUsI/O2oEaECyKf76Efl3PzVlC4fxnnxbT1rH3jOl1H/em9MZXmSsp3CCs6venODsOLHXSd3+szeE8gDoCavC5FBeFGMGwDgpeyf1QJHfknlhtoPMq7faJSMKwbM5uDPzg7kJKnVVIm46LiGFAO3jKckogn9+gqh02TCr79QULgKv7YbhqVDDQPb19/CPDyH8GribhjU1++KkdAihIIY5lH/3oDeDSgg9+dqGqFQEm374Zkv/zjaiEEoh9vuj+fkUhienN+QoKZoCNH1Qoba/jfTa67YXd6MGLgTspOYvQz09UtvfhpHNjW14xgAADDcNENqSdbGnZga+cI4SlDHQdAZsbVO/l4wNsKxI2trrAOhrr4+MI5S/fYLwdNO+ABCVi8i9/bHt87mT0tdilyGEgJkW3IVlKClAKHuW/aVjngC5RXbpCRutTtfZoHruHsL4G3JP2i20ABD7XltDWhmGKH/9hOIvf4zSx5/hnxzqUfNrzctxu132mGeLFAIyCrV21w1Ta8I4Mhtvrq4PQmHPzMPIZAdwpqMP5Vyrzg9wESacw11YbjluTk6DsP4tvTKKGgHadaJKCfbMXPNBQrU/bw83BoRSUG6MA7QxLVDG4MzMtxwnjMN4pD4n4bz1OofutR124WNgnEm7N51S09x2W3adMo5R2f3atDAK30N1fxvOzLzuU8HgmpnH9B8ZR6gd7useIKVALRvp1Q0wy9Z9KZSCOylkN95BKan7QQaaBRrzVAgh4KkMspvv4B0fQkkJa2IKRjrT18bkevb+Jv7xITKb72BmC3q60zBh5ifGmds2XHnXYmDWTVfnIrVUjxBAMp34nO4l1LKRefUGtf0diDCAkcrAXVh+tKcpIQRGJg9nYRn+8QFUHMNIZ+EurQ68F/A+jL+N94Qw1mTqqw+StrtO7Y/YajMhvBpo0sBMLXskovgxT0dJieDstElrTAY+yp/fI/fmyqz+JUyxvjT01FgaqeV1HZwPIADqND3J01kQysBc886+2peMjCOElxcIzo4BQrT9XjY3kMBISQnh11D++qkxHcpTaaRXNkYi4LgPumUhi8yrN7o3ktInb2oo57Anp2HlJgAogNCR2YyMxlkOAZRxXX7KFRBenIIYBqzCVNsv6q2bLKL1Z5xBNTOP6TsyjrRi/g2UiCHCcCgbiNsh4ziZDBxn9x7KIN8zQhmcuUV4h3tX52OY2vt0/FneihQxvMP9pu9vbfcb5Mw8nJn5vpds61OJ1ydk42oFtaM9uPPLz+rz7HYQrAc2Rq/EPg7SHkB9V8zd1O3pbspg5AqIbohv8nRGT1bNL43LWC8EEfgQHdTy2yGFgIojrSdFGcxMTpdXOtwMZBxBhiFE4IE5Lig3u75D1H6LZQTnpyCU6g2GZQ2VltCYzlDOYU1Ow8wVEFXKoKYJbrsju0msCwTHiXsBd1M90+1TQiI4vylTAvinR7Anp0FofzdYMgqbArQ64eU53NmF8SDaM2S8yj6Cu/oRKGNILaygRgjCywsACkY2j9TiyshkTcY8He0j+RHcTcEsTMI/Pmh6nDAOZl5dD3VV9urO18axGqHIbr7VE3c3f39i1hxXr7wAzfwE3IXlru1CpYhRO9xDeO1GFZUukV7dgJHNjwWdRwTKOMD4QPTiuolSCrFfQ/nzh6uBLUKR2XgD7tyxeX7UC0q0tWuSEnUbaSm0pVNfNi0jPKU4COoC3CLwwUwbhLOR698bB2k9ghoG3MUVuPNLyYGn19W7gYxjLWiplB6BH3AT7HNGCQEZBgjDEOn1TVgTUwguzpoGB643wyoRo7q3deOXSFR3t5BZf92yuISlYlOABugdtTU53bWFSAnZFKDVqR3sIOumxz10Y/qKimNUt780T9Qrier2V2Q33nX9eiSUghpGyzQ2sx0ABFG1DP+kPhQyrYdCehgEUMZBLbvFVcOenu2bTduooIe1mjeYRq6gkyUjFKiNP9Ueonevgz6LK2QUorL1BXFN39jrdj80mTB8yUghAJmUEbpmbK4a/618+wR7ajZphgWo2Tr+rYRoa8AsvFqLuKgUoqWcXicsXsJIZbpw/oCScdvjMgwxKEPoMfdDxrGeFO7a9Tx4lJLJtdeMDAOoNlJIT4VwA6mVDZS/XGXuCGVILa9D+DVUvn1qPPf/Z+9Nehzp2jev6wwxOTzmPA811/M8L2LxF0uEBHtW9JJ/S7RafANagi1SfwOk3gG9aVggkFgggcSSBUgsmvcZaq7KeXJ6dkScgcWxnel0OCud6bTDmfFbVYVziLQj4tznHq5L1Gum33hl/dE25NSykNt9g+bBN0TVSmegbQVOaT6VNLmBDNoDG8yoUoYozsEulIZ8V/JIg7RngpISzcO9XoAGXDkh5F+9600YPkdUFKF5tIfw0qhS26UFZJbXHtyzQxgHtR0jgdDx4myfHsGZW4S3tjH4DUNKFuY8+oNoQgio4wCDQ8RjLWlRxs0kzI0gkXn+TyZkUqaFkhKy3ULrcA8ybMPK5k3gYNkzvxkjhMRej4/lpUwIAfcyKL77zehaEgLuetAgaHz9MPD1wfkpvMXVR92cM9s208KdDd2kfXR/xpVciR7jhtc8p7vyRHf5m7vP85sElxewcgUQSns2c7LdAvezoLaduCxbGqQ9F5Ts9MfdOByF0FIBybouJ4YSwpj51q684sKLU0BJI6/ygB2x2fW+Rv3bp54lmJUvmam6mICMMAZnfnHA2cJb3RxQ4SaUwl1YRnB+1lf6IZyP1wuRMWTWttC8XoalFP7GduIeZikGFQZ9/qXh5QWieg2F17/MfnmadqSQTo/6DrsLy4/mhUooBaF2n32QikLoGyXQLsPstsZJ0qo0XZQQEPWqcdcRAla+gExng3BfjOxIC/UfX0yZt/PsM24sw69nasVLXFHLBkinZ/jrhz7rNitfTNyzLQ3SnhOUACqmRDXbm+sHoZXqC9C6hJdl00/4wAchc1zkdt90SjEEhA3vTaSMwVteA/dzvUlKd3EFzI0vR1NuofDmFzSP9s1OMJOFt7x6b9HH2HOiDHaxBCubQ1i9BKEMdr6Q9r8kFCUlWscHA8e1iCCa9Zkq88RBGTP3hOOifX4CAHDnl2Dli5Mt6XaM0q/7MZsTpBN1k5gUKooQ1SsQrRbsXL4zST74nBGNGurfP/f+H5bPIZoN5F+8vXdlQkuB6uc/r1pBlEL75BDMceGU5od+n12cQ+vkoL+FhBC4C0sACMJKecBbN6peQraXQbNpkJYyRpSUpp9JK7Pri0kFE8bhzi8N7ECZlwF5Iv0q92NYX5Uem8f0KA8nyi04xbmOHdTtmmSEUjDHhb+xYx5ElD7KQtWdDPQWB61VZhklTCaEsCc0PKMVtIjP8AyztpsESkroKEK7bLLEbmnBmIzf43qlnMMuzRvvY0zn86Pcgr+5g+rHP/sy2f769pPbwKgoRPXjH73rJzg7Bs/mkd3a7QvUlIhiNwgqaENF4b2DNNFsxvbqts+OYeXyQ7Ne1OIovP4FzYMfEK0mmOt1Jt/50M05AIS1S1jZ8fT0joOndTU9A5SSQFcnp2NH1T45NLtKrUEYh7+5C57N9pXUTFZmGVqrXonMyhXgrycrtTtpCKWxO2KeyU61z2OUMitl7E76SCqKIFpNqDDoafbNiur2OFFCIKpV0D47AaDhzC3CLhSfxH1AGIddKPU0xK5j5cZYBh8BrRVEvYr6t0+9Y8HpMfytF7DzxXvdZ4SQsWaM7wNzPBTf/YawWgGUgpUvgDwxT1KtFNrnpwMBvqhXIYN23z2jtTaC1zEoGX/8jmcx5PDtu2hCOpvYrRfQSoJcdxlQyrj/xARq3I136JgWz+8JPcMoEaF1ctgLsrifQ2Z9C2Gt0rtgtRSof/2Awru/AXb/wk25BW9l/SojkhBZkGlCuYXs9kvUvnzoeRyaG3v3SQUwKgpR/fRnn4+jM79k+uOe0N/5M4xF10nfjr+5/w0yaMFbXp/5KUhCCOzSPMLqZZ88i7eyPtDXOCm0EGjsfRs43tz/DsvPTlwQdlx0e9Xc+cVpn8qjobWCaMRMJwEQ9XrfFDllHHahONBT2x22uC8845uExI3pXWd+6U5Zy7hNrOnpXUJ4cWYkqbpfa9mwsvl7n+tj8HyezjOOVgrtsxMEZye9Y6JRQ/3bJ2RW1vt2qQAQ1atgc4MPD0rZozXYzirMcY2xeedmJZTNrBp7HFoptE+PB4y2g/MTuPNLwHMK0qRA60bJHzBTee7iypNQbO9uPJQQUGFoehoZm9qGTGvd85nsOy4FdFyPbEpiIISCeZkBPUZg0BO260YiGvWrygQhyG7uPui+Iowj9+INGt8/m4weIR0HjYeJaVPLQv7NL2idHEG2m7D8nBlGSNiz//k8nWccLaUx+L2BCtqmp+zGWDohTyflPgnMjZmsm3NcaCkR1auxr4lmHcydbRX6UdBax/a3YNjxGcWUsi3gARmMcWEkE9iAnRFhDIQ+kV7AJ0p3ijwsn/d9fsz1wL3BsiC1bORevDFyGVIYOSDGHmSDSCgFz/jIv3oPrZS5ZsYg7UEIBbMd+GubphxKWSJL1WmQNkPoYTV4DZgRzc7rhI5NzDTlCUAJqG0PTqIBRmvtEVBCQAsB0ayD2g6Y4yZih0oIjVVsJ9bT6iVKEoRxZFY30dj72nfcW9l4ck32TxFq2ci//hXBxQlkqwUrX4CdLw29n3sbhDFCCHk0+RhTtk7uvZ/eIbMCpbCL80bD6xqEWx0DbgItYeyGNnen1n+Skjwo4/BWNhDVqn3ZVuZ6YPb4s2hKCDPMcnZ89bscF7kHjOGPC2pZyG7tovrp2kg/Ichuvph6I/pThVAKq1BE3ntvhjU0TFnJcRK9OKYYCCFgtg1veQ1aaRPUPJVp6BkgXckngBICKgohmo3OwuiMvFhRxpBZXoMOg17pilo2sjuvQG0HhTe/QuuOEn0CMhY/Q4mo0zMTgLneVHtm7kv3/IPyOahlwS7Og/JkqX93YbZjxtGPD6DCEFa+AHdu8VGuFSWivgANMBYt7fNTeEsrU39/mOOh+PY3iGYDGhpWJmtKb+nC82hQxkE9Dn99GwCmfg2kjA4hFGT2WzZnjtlaFWcQJSI09r/3+SyyjI/czquRU8LUsnrjxAMG6TPU8KyiCPUfXyCu9Um5SytwF1ZmZtJQCYH22THaJ4e9Y63jQ+RfvYvt1Zg2XakRf2Ono6f3eP0Xoh4/DRbVLuEuLE59ge4pyBdmc6pwlpn2Z5+SMmukd8wjI4P2gBG2bDYQVi6H95jdAuUc7FqPz6zt/qWIEFYu+gI0AGifHE1VbHNUtJJ9AVrnIJoH3we0gpSSUGGIsFJGVK9BDbGTmQSUMdBH1nIa1udm7FjSR05KSkrKXZmNtMUME1XjVY2jahl2ce5Zqf0rJSEadYTVy9jXo+plIrNQcQwLtJSQ0EohrFWgAiMaC61R/fA7uoMdxLKQf/kOzH6cpv1pw93MlbF8D2I8/J7R9f5c0EpBa51+tikpj0AapD0yzIlvzKZOvB/jU0ZLCVGv3WLjMTvlp9heLkKR3dxB7fMN0di5RWRW19E83AMA6ChCc/+7EcxNaB+e1hpaCFNaJ2b66a6laGpZyL98i/bpMaJ6FdS24a1sgD7RoHSaKCmMH+8jWYLd/rsldBSidXoMLQWc0jy4n30Szg0pKUkhmSvEE8LKGauQPj+9jvbMs+vP0Bph5QLZrZcILy/6XiKMd/wqZ4Susnv5vHfILpYQXF4MisZenCL34i0IZT3B3KheNYvrmNZV3ZlUHMc1pbWGDNqof/0AFZoStJUrwN/YufOgAbVseCvrcOWKkQB5xGBUK9UTSyV89loA7oNWCjJoo3m4Z2y+/Cy85XUwe3IbHdluovbpz97/o+ol7NICMqsbY+kt7Q4XaSnBbDvWkzgl5amTBmmPDLUs5F+9R/v0CKJRA3O9jhXP89ttGiV/B0H5DNnd12ifHEIGbfBMFpnVjZmSQCAgsHIFWNkcwmoFlDE4C8tofP8c+/Wi1QB1XMiW8VQc1+ffy2acHQNSwplfBHMzD1oktRCoff6rb2MR1SpoHR/AW9u4szDlJPSHVBShdXKA8LIMwhjcxZUn48N5GyoM+kroYRggqlVReP3LRKa7lTDZ4JuE5TN4y6t46NKiohC1Lx+uKddTZLdfwsrm0kAt5VmRBmkTgNk2MqsbvdLRc+3doJwbjarPf0I2G3DmFkBsB8z1QG0HhBAoKQEloYToKJKzxE58Ng9+gHIOns1BS4WwUga1nVjRWGbZfUHPOLwUtdYQzTrqXz70joWVspmUXVy993WmRNSf+e0QXJ6bBTghtmJKRKh/+wTRNJY1Wgo0979BawV3fvHJum4oKdE6PsRN42ktIkTNOpxC6fFPQpuhqNjzE9FI/ZbGfJv0rlclJZpHB/33kVaof/uI4ru/zazXZ0rKfUjm6vcESbqq8aSgtoPCq/fGNgQazLJ7JSolBMJKGc2D7z3RVbs03ymfJCszQjiHt7xmzLk7iwm1bPhbu4iuGd4Dpi+ROi5ACJjnw1taAfdzDy7LaSFisxntk2O4c0v3l2UZcl5JC3q0lL0A7TrtkyM4hTkQK1nnOza0HjoJfbPU/mgQAp7xYz0dKb9bEKWEgGjUEFycApTBW1wxk8FKIYobLtIaMghmqnf1vigRmRaGm1JLKc+ONEhLmSjG3sOOfdB2MyHXCcvnsLJ5OKX5SZ3inSCEwC6UQBlD6/QIWkrYxXkwqyMae7QPFYWwckWT1WEM+ZdvAUL6As6H9ZLpIYuyhlLy3vo6lPGY6UzAmV9MlI2PHuK1qcWgmfdTgjAGu1CKDVCtXGEi50A5R2Z9G9WPv/d5nnorayDs51eeyQbuIzi/clCJKmVkt1+BZTIgnMWasj+HaXgVhWjsf4flZ8EyPgABqhSobaeB2jMkOU/clGdPWK+CeT5UGPQ9oIPyGax8IXGTkJRz2MU58I5PqinPmgXK39wdEI29XqbpuhUYZX7Ss8kZ7W8kYK43WF4l5EEldWpZyL14g8aPLyZTQgic+UW4C0uPmg3WWhsT5zuev3F3uBrG6GLlC086a00IgV2cM3qDzUbvuLu4PNGMM7MdFN78hqhShhIR7OIcqGXf6RrWUvYFaF2ah9+Re/ke3tIaGj++9P8+10tcRn3cKCnQOj2Ct7iC5vE+xOGeGVIqzCGzug7yDLKIKf0ka9VLebaoKAJ3XKBQAvcykGHQK3sSymAM5JNJXKO2CTLiAw2tTP/a9axheHkOf2PHaOfdMcCgloXM+jZqn//sK696K+sP7htjtoPs9ito3c30sZEDv648xPXgdejXighh5RJh+dyUkpdWQR331t9JGEd25yVqXz/2sjnUcZBZ23ryGRdqWcjuvIKKQsggAPcyIIxPtH+TUApm22CLyyN/783AuosKQxBoM028uYvW8QG0FLDyRaOzNwOWdw9CaXDPR+NaGwW0Rnh5DkIJvNXNifU0a6WghEBUuzSVgkIJhPPEbZafOum7nfIoaKWglQJh9Ke9TEpEqH37CHktK2AXSvDXt9HY+2oW7Ce06Gop0Opopl2nebgHK5cfqTGaexkU3v6GoHwOLSWc0nwnm/Hw9+u+C75WCjIM0DrcgwwDWNk8vKWVob1ESgg09r719SFF1Utkd1/DvqV8RygFz/govv0NMgw6QybW01/IO1BugXIL3POnfSojQxkz7hO6v2TNvEynJcBkqa1sHoAG7rFJ6KKVAgiZkVKhHjp8FJTP4S2vTcwCUAYtVD/+2fuMWkf78De2YRXn7jzhPQ5UFEG0GoiqFbBMBnau8Cz6ErukQdqMoZSEFsL4IxJiRtITpB9kRFAjtM9PIZoN8EwW7vzC0JtKa42wctkXoAFmStEuzSO7+3qozdCsopWOzSRoKUa2CjPZDAeZ5bVxnd6DMfIQf+9l94Kgjah2ifzL97EBlJYitlG8dbhn3AtuCbpMOZnN9EO7u6EBJXda/LoT0AA6IrYz+BhnDJm1zf4eVELhb2z3Spqmf/X+AbeKIkSNOqLKBajrwiktJt5KzzzLh9jGje4ieG+UiNDY+zYQRDf2f6CYK0xswltFEerfP10NqFwAbctG/tW7sd7zWuvEXhczeHc/X7RSEPU66l8/onfHUor8y7eJ2U1rEaHy4feehIOoVxGWT5F/9T5+WEDJPm9Tq1CCU5o3vUZamyA0oTfPfSGUgDA+0Bh9XyHW7qKtlTJTxFMM2pWUaB4f9JVfAVPGEq0GbKs4+D1DGv1lEGCiK9MUUFFoNjT1KqjjwVtevdVbVYkIraMDBOUzQGtY+RL89c2ZC1IpNcMPVjaHsFIGoQxWvji2cq0SEeo/PpvNLABUgOD0BPk3vyTajq17/8YN7tjF0uTkb7SGbDVjjisoKUEnlKyWQWtggtjcM2fwllYe/JxTIoJstxGUz0Ft21QiHtnbeFTSIG2G0FJ0mmmvLVxKofHjRaZviAAAIABJREFUK3Iv3ky9qVZrjaB8MaCxpaIIYfUS7vzSwPcQQo08Rb2KzNoWtFZo7H2FFgI8kwWzdkAd50kFaoRxZNa3BoRv/fWtkbXTlBBonx6hfXoMUxai8Ne3pzdooVXPpeAmw+QhmGXD9Bz2B2SWn33ShuwqilD9dM1CrNlAWLlA4c2vsYFEVz8svLg2EVktoy4jZLdfTv3+HxXKOdDpPxw3KgyvArQOWkm0jg+QWdtKdPsEsx3kdl+j9vUjVEeLjmdzyEywHw0goJYdK/VCJljqjG58hl1EowatHjbIpIRA6/igb4ClfXKE/Ov34K537587bp7uE/AJct3+5jqy3YJWCcg4aN1T1L+JaDZiS3mEUriLy2CZLAilaB3u9SQURLOO6qc/ekGfKV/UEFxeQIaBySDNIIRSWLkCCm9+hbO4DGdxBYU3v4Fn8yNrkYlmHe3TI/QCHKXQ+PFlajIUhDHY+fg+Mp4dYvvVKX3d/DmZ9a3EChmPA9GsDwauSqF1chQrL6KVRFg+G/w5jfpQOZLnimjHZIEAkx1K6Hulte59jsxxkX/xFoW3f0Ph3d+Q3Xp5515LJeWDrwfC+cA9CRgZnkkGuDwTXyHinv/gbJdWMRPGWqF58H1odn8aPN0n4FOEUsRlHAhjw/RHJ0o3+AivlS+7WLni0GwY5RaymzsDI/eAyR6KVgsc6M86AMisb5ux/wTviodBGQOYB3918EF4V9QQGQPA9PQ9RobiZxBC4cwtIqyU+5qf3YXh8hCUMdMknssjqlVAuAXLz86UTdh9iGsOBwAVtKG1ArmxhybAQBm5x4i9jE+dYe0fzMt0nqPJQWsNFUUILk4hgzbsQhGWnx95AEaJCKJRR1A+A+EWvIUVENu6V5M/IQQ8m0P+1Xu0Tg4BpeDMLYJncxOdnOaePyAzRBiHMwY5oGGZfdlqDvTiTZM0SJshCKVw5hcRnJ/0HXeX1xIjMmrlCmBepq+fgWV8U7oagnFjYMPFSZVE+/x04KZq7n8z4p0zGKSNjWHuAFNciLo6azIIjPl3xv+pPES39MUcd4JnOl2sbB6t44PB47l8fEmJ0E4gW+07TG1noiWoWYBaFqx8AVG10jtGGIO3tAotJRSQmM2dikJU//p7b5goqpTBM1lkd+5ewlZCoHmwh/DyvHcsvDhD7uU70FuevbdBGQfNcKP5CD2V9gmtNTJrWxCtBkSjDua4pjdvDFkJasX3JjI3k6g2i2Ss7E+Qxxj7pozDW14Fz/gmg0II3MVl8E6pMAlQy0Ju57W5qZoNcD/70wk9wKTXndI8mgPSFMZ+pnnwI/b7ZNACs2eraXpcUMbgLa0MTkYSAis/2KA/SbryELjnAvEcoI4Dq1DqG5xhjguntBD73KCcw1/fMXI1nU0Q7fQvPdQH9qlBuQV/Ywei2URYuQCzHVi5vBFobjbgrW7AmVvoCzx6Azham17ZSRjVd/rkbk57i2bdWGDdMUjTUvYFaF2aBz+Q2331oH7FaQWzWikEZ8donx2DZ3NgjgcZtFH9+Aey2y/BYoaQRoEwBntuAeHFtRYCQpBZ20xUm0VyzuSJoEQE0WoiLJ+DWrap4Y9xWoRyC05pvmf/kqSLqQu1LNhWEfYIgQIhBHZpHlGz0Vu0CGXwt3Z7D0wZY/o9a83S44Y6LvytF2ge/IAWEZjjIrO5k8jrYtwoIXpliSTJ0NwVyi3461tQiyuIGjUw1/vphobaNnI7r43I8C2+jibgUACjE9W0ShKUW7ByRmctOD/tM6VvHe6Z51MnSFMiQuvk0Gx+tQZzPWS3XoA67uMOLSk1tOwtW81bKxB9P0bED+vIoDWzpXCtFURnMyLqtb5BENFsjrS+xEE5R2ZlHU6hhKB8DmJZcOeXEvfsTNbZzDhxKef22QkKr9+DjXlaJGkX0jgwi9Y29OomoKTptessvt7KBupf/ur7eub9PEN3F7SSxqy71TS6Y457bzmM/p9rBj0eUxqDMm6kDPwcAD3gDToLdAdARtmxyzBAc/8boloVhDG4C8u9DdEs0ROkHdIgHfs9t1zzujNd2zo+gGy3wDK+EYO2Rvd9VFHUyfAQEEZn7r0FOsLRx4exA02i2QChDDIMjNH72VUbiWy3UP38Jwqvf32QVtvPIJSBZ/xYuYvRron4agLP+Ikq3Y0CIRTcz0E0Bic8rex4MvSUW6C5grH2S6jg8dNb6aeIlmIw5awVmgc/4G+/mE3RyQkzLPjkmQxyL96idbRvfAILpVub0e+K1gqi2UTty1+wsnm4C0umzKC16aO6Z6pfCYGgfI7W8T6gVGdacRtWrjD0Z14FdbqnpXaXoO6hop+TQCtlykiU9h6ESgqoIEDr9Mg0Js8vgmeyP92AqChC7fNfvR5FLU3JCJTBXVgceUL2KaEigcqHv/cmGGW7hahyicKbX0byfZRBG7UvH3rvMfMyxvx81loLOu4FN+fACTPBUfXj3+GtbCC4GBzA0UJAhsGjlj3NdPsqwkq5byLbyhVAR3ivCWVwl1bRPjm8Okgp/LXZnZAmlMKdX0BYPuuTAuF+buxJjyRn4Wfz00soRnxzENFumh6151l1GAuUcdBsDmznlTEuH1NWSguB+rdPcErz4H4O9e9fjMwJIXAXlu9tWi2DFlqHV310Wko0vn9G4e1vsYMOSgqEl2W0jvagpexpqd0W1CWBn/XxGP+/CO3TY6iwDStfgp0vgnCOqFbt04qLahW4iytwf2IDpkQUO5kVnB3BKZaerQm11toMFd0YwNFSIKyU4S7czWNTRZHR6Lr2HstWE429r6YEOEOLvunjXUNUq/Qdd+aX0Do5hIqiuIH5azx+qZBaFgqvf+lNRNuFkqkSjPDcoZzDXViGXSghvLwwLScdr81Zhlo28q/eI6pXIJpNWPmCaQmYwazufZntTzBhsCH2RffVdFEiMsHdLb0nz41xLxDGkkfCKS2g+umPay9otE+PwDM+7EJp5J95vXRynaB8jszK+sBxFQR9FjlaChPUvfkVYMkQVuxafolmA1pKcD+HqFlHc+8roDWo4yK3/bKvj0dFISp//b3XOxbVqgjLZ70+upu0z47hLizdOrGrh4zHP3utMK0hO+KnN5Ht+OOxP0apnojqdUS9OvS9nyZaK2ghoZU0WVTWb5VFHRe5F2/RPNwz08Z+Dk5pAbXP5n6PqhXYxbmO3uAVhLGJuBOYTLh95yB6GJSbCWruZcZ0ZsmAWhac0gKc0R7DT4Y0SBsjhPHBaRFKkVndGLnUqaIQ9W+fIZrGEoN0piaZ6z37QG2sEGPSHcX0PQCmp5BncyN9frcGCzGfnVYK7fP4oK59cQY/RlRyGqgwQPXjH32Cypm1TdjFeVOSCNqofvqzV1pTUiKsXiK7/cL0/gRtBGfHEM0G0An4Brgm6DkMZtkgjEHfEDO2i3OJkaKZBoRS2MVSrA/qSBuNYY8XQoa+NC20khDNJurfP/XKhXZxrjOhZ7ItlDHQbA653VemiZ5Ss6mwHeOGUikjt/MaKgoRXl6Y77EdZLdfznwmKmX2SW4hdgbpTovkXryBXZqHu7yGwpvfQEfcjSkp0Tzc6wVoAKCjCLUvf01NSf6pQhjtNY3Gvk4Ihq9ag6goQuv4AHZpPvZ1pzg34gmO9uWPhRICjf3vA44XzcM9uHMLvf9rKSA7tlBaShBC0Nj7itrnPxFcnCKzvgWezUEraezAbkLpT7POhHFkd1/3BWTcz8FbWnv03hIjPBoiuLxA++wYMmj/VJ1cKwUZhmidHKKx/804DcQFqGPA8vPgNyYCrXwRzLt7NpZQBp7NDRy3i3OT8468I1rKgedieHmBoHw+4HBCuQVq2aZ1glvwVjc6P0Sj9vWjUfl/9R6Ft78h//JdZ0OcLpEp0yXdJowZyi3QrAXuP8AYXKlY1X4tBJQUE9HveS5QxuEuLBkft6P9gXF1d3H5zj1hSgg09r4iqlVALQuZtU20jg+hpQCxLPjrO7Eq+oRSuAtLCMuDOkduaWHg2FTQasAL0RzXUFKY7MSNDJhst/pKmrLVRP3rJ+R2XwOEwd/YQe3zn33vub++/dNsGKEU3PNRePOrCRo7gd0k+lQGs4k/TDaxtDD0OpFhgOqH33sl3+D8FO7icqf3bryPYGpZyG69hIpCiHYT3PNBLWvk/qbs5i4aBz8QVS4BAtileWRW1hPXHylazViJieDiDE5x/taBGuZ4yL/+Ba3jfajI9KFSy06frymJYipBGiFkDsC/AbAD4CuAf6K1Lt/4mn8XwH8DIA9AAvivtdb/ZrJnen8eWpIklA6Uc8bxc1MGodwCCEXuxVs0fnyBCgOjTr68DjbEXiYOrVSvQbl1tA+7ULrSebPtW2UQqO3A39hB8/CHyUBxjsza9sSb4JUU0NL06dFrEigAAbXt2IZ9yngvQCOMg9l2z/j9JlpJyKAFK18CsW0U3v4NUaUMrSXswpzpuxxlonWCC6qSAs0h2US7UIofCBHme27azLRPj+HML/V0usYJtSxQazRZj8GfYcPf2Aa6pXbKEhegARia6brLc5IyBupl4G++uBpGSp+vKQljWpm0fwHg/9Ba/0tCyL/o/P+/uPE1TQD/qdb6AyFkDcD/Qwj537TWgw0XTwzCGJz5pf5xasCk3xNWbngqUMZAMj7yL98Z30RydwmMK/p39GGl3MuIFt79O7cuAJTxnn+lmZQknUGRyZVblIjQPNy/MvGmFP7GDqxcwQSNqxuof/vU9z1WrtATnOwODhBuGSmRYQ3+IL0BEGbbYIsPa5ieFFoqRI16zAsaMgzjtaq0gojR6AIAFYYTaUy/L5TxqUykKyUBKaFhgq3bsoDMdUEYHwic3cWVO/eTmeAzfa6mJJNpBWn/MYD/oPPv/xbA/4kbQZrW+q9r/z4ghJwAWATw9IO0TvkLWpuGcqVg5QrIrG+nqfhH5KF6Y4TSATNgAHe27TIeptOTj+hOXvZQykyYvvsbKHPAszmjVXdiSrhOaR5WYQ4EGla+0C/BwTicuQU0m4MBipXNT+gvGg9KCoh6HVorMMeJVYgfOnVMKLjrmWGJm9/zTKVCbqMr19I+OwG0As9k4W/uDPV0JdxC/uVb1H98hWw1jLDx4orZWKRZsZQnwLSCtGWt9SEAaK0PCSFLt30xIeTfA2AD+HTb180SRrhU9sQWb0K5BW95zQRrAEBpKoabcCi3kN1+idrXD1AdzTzmevC3dhOvLaWEiBX0BIxEAVtYutKq8zwjC3NLeYgQAjtfhCg1eoEfoQz+5i5IAstmtyFbTdS/fQTP+HCXVvu03QDTmD/sb6KcI7O2ZeRdrvVO2aWFmXsfHhutFIKLs74yuWjWUfv8F/Kv3sduUAkhYK5nJjeVBshsWoSlpAzj0VYOQsj/DmAl5qX/csSfswrgvwfwj3pI/YQQ8s8B/HMA2NraGvFMJ4+KIrTPTxBWyqCcm94n1xtYyKedWUkZHea4yL941zNMJpTNRvaTDFfdvhlM3HWzQLmFzNoGvOU10/PzSNZYj4kSwrgZwNgI8VYT2Z3XCM5PoKWEXZyDXSgOtd7RSoFYFvKvfwFghikINbIvSQ/cJ42WMlaKRkUhlIhu9zR9RuKmKc+LR3tKaK3/o2GvEUKOCSGrnSzaKoBYkShCSB7A/wrgv9Ja/1+3/K5/BeBfAcA//MM/JNpNtqvm3fWSUwFQ+/wnsruvYXdM01NmG7OYzNiioU0fT1Sr9h+nFFaMHMNdmVZf09jQ+mqAhxCoMIDO+HCXVkAoQ1ivovrxD3A/C29lvW84RCuFqFFD4/vn3s+4qeGVch1tsmGxL93+WNdad0S/Z2cDkJJyF6Z1Rf8vAP6x8+9/BPA/3/wCQogN4H8C8N9prf/HCZ7bo6JEFGv22zraNxYlKSk36GpzyaANFYZG8mKMKBF19LsayKxv9frymGcGKZ6zoCdhDHaxZKZ/d16DOi5ahz/Q+PEVUb0KbjtQIkJ4eWGkOa7pn2khUP/6sW9Ke5iGV4opUzox+oKEDc9Gd++N9ukRGj++ICifpc/RlCfFtJ6+/xLA/0AI+c8AfAfwnwAAIeQfAPznWut/BuCfAPj3AcwTQv5p5/v+qdb6/53C+Y6NYcKXxkA2fXCn9KOVgmg1Uf/2qRcAjDMb0+0DiiplRJUyrFwB/tqWMZe37URPH04CQimc0iIIsxCUz3qK9ADQOtyDM78EZ27RlD9FhKhR7wkWR616bAYoLJ//VMPrOWLMxlcgw6DnmkAtG9mdV7H6goCpTFQ//L033RlWymCej9zOq9loM0hJ+QlTCdK01ucA/sOY4/83gH/W+fe/BvCvJ3xqj86wKSUrV0icmnfK9NFSoPblrz6h2PDyAsz14C4uP1iiQ0uJ4JqNWVSr9LTesjuvnmyQprtlTEpAf3LfUcuClcv3eat2CS7OkNt9ZYzNgT4duaFyOYQmxkkiaVDLgr+x0/EsVrd6FhuP3OMB+Q3ZakC2W2mQlvIkSAv4E4Ywhsz6dt8xatvwlpOn5p0yfUS7NaDkD5jgQItBseP7MHRg4In296goQvv0CPWvH9Hc/w4ZtHuDHkMZVp7UCtcjLu5f9e9xNxPrnuAtraQ9abdAuRFEZo4LallDJ4hNljleg27Y8ZSUWeP5NptMCcpYT7RUNBug3Oo9jFJSbvIQRfU7/XzO4S4uo/Hj68DxYVnfWUZ1PHB7WmfNOsLLCxRe/wLmDve3NFO6dqct4Qrmer3smTO/1JchI5wj//IdGntfIJoNEMbhLa/1BXK30cv2kbtP1E4KrXXHL1NPzY3ATMlmIWIEhh/itpCSkiSSdec/EyhjAGNPtpSUMj6YE6+o7iwuj6WhnxACK1eEt7qB9skhtJQ9AdFhfUCzjAzag2K0WqN5fAB/Yyc22NBaQ0Mj9+IN2uenRk9OGRshf3MXMmgh9/IdRKMGdk2g1mh4ucjuvOpk4ggIY3fKUCoRIaxWEF6cAZTCW1wB8zKJkO0w4r41NI/2ocIQVjaHzPrWxJ9nXdHvoHzeN7DB/SyYc3dD+VlCSePGoGQEwiwQlupnPnXSTzclJcGYbMw1RXXK4C4uw84Xx5ZNo5zDnV/qNbyD0EQEA6OioghRowYZtGHnCqC2M/B3yKAd/71Bu1O67A/SlBAIq5e9ANYqFFF48ytUFIFyjubxAWSraURr17djA+dRS5tKin57LgC1ehX+5g7s4vzUlfRlZ5ClS1SroPrxDxRe/zLxigDhFgqv3yOsXEK0GrDzRfBM9klWJrqC062jA3SHzJz5JXjLaz+9X1UUQbSbiKqXYG4Gdr6QOl7MCLP3JE5JeUZcV1TXSoM8kqL6rAsnyzBE7dPvPfmF9vEB7LkFZFY2+hYw7mdjv9/K5gca/bXWCCvlvoGB8OIMstVCbveVyaStbgLQHeeQ8QQGWqp+e64OzcN9WNnCVKdCjbjv4cBxLUwQYFuT1Xo0Vm72lTPLE0ZFIVpH+33HgvMTE3DdorGpRIT6jy8Q9SsNxNaJhcKr92mgNgM8zc7glJQZQ4kIst2GaDagotBMt12DcgvMto1Y6hNt6L8vWim0Tw8H9LHCizMo0X+Mcgv23EL/Mds2k7I33lctBNonBwO/T7Ya0EIa82/LArXs8Q4CDBliMCW9Kcv0aD1Qeu+9NEReKIkoKSHDAMHFGcLqJVQUJV67Liifxx5vX5wNPC+uI4OgL0ADAB1FaJ+d3Pp900RJaUq7KWkmLSVl2qgo7LhQNAGYJvXszss7G7M/d7SUEPVa7Guy2QC/NhBAOUdmZR3u/BKiehXMccE9f2h5bJiu4U+nQR8AYQygdGCql3kZYMqlTsLN4NPNjA4wPEt5V1QUQUsBrZSZ6nwkCzElJcLKBZp7VxnS7pBHkodlhpU0fza0IZrx94Zo1I1tWYKeMUoIyFajYw9G4C6umMG6GWy/GBfJ+XRSUp4hSko0j/Z7ARpgAoDa149DMxbPDSWl8W+MwvhsB6WgQxbXuOOUW+BeBt7iCux8cXj/EqWw8sX43/eIJUfCOPyN3YHf6W/sTF26gxAKp7QAft0qjBAzaPKABnYVhah9+QuVv/4/VD/+jss//y1Es3GvTE/XhSCslBGUzyHDoD8roySa+9/7v0cINA9+jN3NY5zYxbnYIN1dWLk10OJu/KQr87xkBWhSIjg/Qe3LB0TVCqLqJWqf/kBUvUxsxm8SPN/wNCUlCSiFqHIZe1xG4bPvGVFRiObRPqLqpZGwWFqFlS/27awpY8isrKNSq/TpmTEv86CJQ8oY/NVNVNstM1gAGHuo7VcPCkh+BqEUVi6Pwru/IapVzf+zucTYc1HLQnbrBbSUUEKA2faDZDiUlGge7vVP3SqF2tcPKL79beReSRW0Uf30R58dV3brJax8AYRSyDCM1b2L6jWTvUyoXCXtSrrsf4dsNcBcD5m1zZ/2KDLXA/MyfRtBwhjcxduDu4mjJFong/2OzcM9WLn8SNeBEhG0EFBKgll2Z6o6oR/sT0jGXZ+S8mzRIIzFls9m9aEyLpSIUPvyobd4aynR2PsKf2MHdql/ypHaNgpvfkXr9AgqCGAXirALcw/OeFHbRv7FW/PQlxLUsiDDEEoIEM5+6lZw79/blemZX3yUn/9QKLcAboGNQ3VDSYTV+I2KiqKRNipKRGjsfesL0ACgvvelF/ANK50x20aSrSAIZeAZ39hkdWRhyB2CY2pZyO28RlirdKY7PThzi4mbgDUuE4PBs5ZipH7Bm+0joBTZ7Zew/FyygtI7kgZpKSlThHAL7tLKQPmFud6z1z9SQgxqmgFonRzCyvVPORLKwBwGf20LumsnNC6JEsuClhL1vU/XbJ8IsjsvO1Ohs/fgV0IYyRE6fp0trdXVEMGdpl4JKGNQcSWtUd9brSGag+K2UApKSlALHVHhdYh2E6Je7QV03upG4gKXmygRISyfoX16ZDQN/awpg9vOrdc7tSy4cwuwiyUQQu91b2itAa0f7XonlJoN640A2/xtd/udSkk0jw/7soZQCvWvn1B8N3pWNgk871UgJWXKEEJgF0qAhplQFBJ2oYjMDCwYj83Nh3XveFfpPgZCKciYW21NduZrny8noNH48QWFN7/NVJCmlYIMWmge7EEGbfBMFpnV9Z8u8ndFCYGoeonm0R60EGBeBv7GjhFlHmY/xjncxVU0D8axUSEg3OoTt+29QhmUlJ3hBAlm23B3XkO0GuBeJvECuEYS5rJvaEM06qh+/hOFV7/cSZrlPplfrRSUMNOgKgrhFOfA/ezY+yMJ4/DXd1D//unaQQJ/Y+fupX4pEVXKg8e1ggyCmWwfSYO0lJQpQ7kFZ37RBGtAJ7vxvEudQKf8RGhHZPYKq1AEJlkKHpKd0Z0FHzMUTKsoRPXjH72yUlQto9qoovDmV5AxLGCy1URj72vf/6uf/ri1t4wQYpriAbRPj6CkgF0oIbOyPvJGhXCOzOr6gM2ZXZwDKIWoV/uEeNunx/C3X4B7fuKDbS0E2mdHg8ejCDIMHm1Tp8IAlQ9/v7pmKmVYhRL89a2BQM1ImSijXzfidC6hFDyXR+HtbwgrZeOGUiiB8uH+rTE/BYQPOrQAnanpGSQN0lJSEoAR5ZydxX4SEMaR3XmJ+tdPvUCNuZ5ZvCf8wCWcx+uAzVDfoFYKrZOjgb4fLSXCWhXuDf24UVFSoHU6GERAKUT1GpzS/NDvpZx3Niqdadp7DiJ0bc6yu6/RPjmCVhLO3EInW63QuCZM3KW59x3Wm+wMlMI0oIb0ZunHmX5U0ky93rxmokoZanmtF6RppSDbLdR/fIEK2sYZZWnF9L6NMPDS7cX0llbvdb6Ec3hLKwNBOnXcqU9G35c0SEtJSUkkhFJYfg7Fd79BhgEIY6DMmoL1kOlhat5Y4O3iXOKzL9fRWkHfMIjv0l/Kve8vwIC2W++lO0godN0DHgrlHHauAO75MIM5HIQQyDCIDbRHbUyfFoRx2KV5tG9OQFL6ePpuSkHE9IUCnWumo0GopUD185+9z18ridbRPpjjXlUIJkA3SPc3dtA6PjBZ2XzROI/M6CY4DdJSUlISS9euapq9JIRQ2J2yS/v0EFopOKUF2KW5mRLZpIzDLs4huqE+D2AsC6nJhi3EloatXP7BP/8+53MdU4IbbEwnbHxDJo9J11BetluIOtOwhHNkt18+miSMmSjNIKpWBl67HhhGjXpsgN4+PX6U/rXboNwEs1auAEA/SB4mCczOEyYlJSXlEegZs7dbsHIFMMcZWFQo57ALRXDfN1adnM/Ewn4TK1+AlS0gql8tuu7i8tiCYCtXgD2/iPD8FIBZ5B8qdDsuCOPwVjYGMqLeykYizu8uUG7B39gxkj3aSHAQzu48/TgqhDFkVjdR6WrIdbDnFvrfsyGZSJOhnPx98pTaR2bjykxJSUl5BLqN9KpTBmyfHA5tigYws30tXSi34G/tQAkBFQZgrtcpI49nKaDcgr+ygcziakcKhSZGSJRQCrtYAvcyaJ8dAwDchWVQx5mpsrXJEE5u6TYahL8hvLyACgPYpbkBqybLzxk3hBvBmju/OLMN+0khDdJSUlIeBSUEtBSIahUQbsHysyAjTWo9LlqpnqzAdaJKGWppdeYDsmFQbpm/zX0cyQnCWGIXZso4aIbD39gBgEQGZ937RoWhCSDHGETfB0IomG3DW1oZ/jWcI7f7GvXvX4z8CSFw5heNy0NC7vdZJQ3SUlJSxo6SEuHlRZ/2FWEM+VfvE2NirZWM7c8CANGogXuZCZ9RyqRIYnAGdDT59r/3aX25i8twF1cT3f9IKAX3cyi8fm+GRCi9kxtCys9J5pWakpIy20iJ5uGPvkNaGmNrFSdlMQ0oBRuSTeoeV1GEsFJGY+8bgoszqGhQJDUlZVyIem1AjLV9ejye6dtHhhACatlgjgtm2WmANiaSG5onnJ6typ1sT1JSfo4SAkpEkK0mqO2A2c6IEJ2zAAAgAElEQVTMjo3LaIiJdaP+aJpOo0Ipg7e0hrBS7muKZq4H5nhQUYTa1w89i5ng4hTUdpB/+W5mP5eU5KKkRHB5EftacHkBnvEnfEYpSSAN0kZEKwUZBmjuf4doNoy45tommOc9mtlyytNHiQjN44PeVBwAMC+D3M7rmQwIhppYOw6SZGJNLQuFN7+ifXoMGbRh5ws9Y/awUu73AITRhgovz+EsLN+718Zk4/Sj+GamzC6EkJ+Yv6c8R9Jy54goIVD98DtEo2b8wFoN1D79CZ2WQVIegIqivgANMJY6YeVi7EKbXS8+peK9MccBYRxWvjhwfBom1iqKoKKwY1nT/14SSsFsB5nVDWS3X8CZX+qd37B+tahRv5M468B5SImoUUPt6wdc/vlv0fj+GTJoz4SQasrjQyiFu7hipiT7jrOJCsKmJIt0GzciYeUiplyj0T49QmZtK7ENqSnJJqoNikUCQFgpwy7Nj0XHSWsNFUVonx5BNOtgrgdveQ3Ussc+gUU5h7+xjbBSQFg+B2EM3vIq6ASHBpSSkM0mGvvfoII2qO0gs74FnskO9MvEGbNzP4fgRuAMADxzP59HFQaoffqz9/+oVkX14+9j881MmX2oZSP/8h2ahz8g223wTMasK2lLzbMlDdJGZFjjsBICGjpBhZyUWYI6Tvxx2xnYWd8XLSJUP/69Z40jW01ElUvk3/z6KOUUyq0r30SCiZf2dBSh9vkvGL8iEyTVv3xA4c2vAPu5/ITl50AdFypo944Ry4JTmh85qFVSDtr5YHy+meNGaw0thBFNJQSE0ESX3c35RhCtFrQS4JksCOMz17xOKAXP+MhuvzLJgLQk/uxJP/0RcYpzCDpCiH3HSwtpT9otKBF1SkQEhNJEj5NPAyuTA7Ws/k0AIfCWVke+rrRSnYW1P5AIq5cD3oVaSQQXp/CW1x5Fz4gQAjKlzzoon6MboF2nfXZ8p6w3tSzkX7xFWC0jqlXBM1k4pbn7qfNrDSXjp1q1SFarhNbaZP2+fOhNFTLPR277JWhCe6NUGKD68Q/oa+9xdvslrFwhcdUNJYUxSqd0aBCZPh9TuqRXwohQ24G7tNq3K7ZL86C2jcbBD9iF0oAa83NHhgHq3z5DthoAACubh7+5m+id+aShloXcy/donx4iqtfAHBeZlfWRAgIlIkT1GqLqJZjjwplb6BOPlUOMkmW7ZSYxn5jo5E2Pxt7xEfrJqGXBmVuEU1qIDXzv/HM4h1Oah6jXBl6L692bJlqIvgANAGSrgcb+N/hbu4nL7Cgh0Nj7Bi0FCONw5hbAMz60lNBKJiZI00pBhQGaR/uQ7RZ4xofXucdTwdeUYSTrbpsBKOdwF5fhzC1ARREo5wirFVQ//g5ojeDsGM78kun1uUegpkTUebgoUM5BGE/MQ+Y+KBGh/vVjX4AQ1ato7H9DdnM3scrk04DZNjKrmya4oGSkxVCJCPVvn81AS4f22THyr38Bs00p1c4XY3us7EJppq+xYThzCwjOTwaPzy+O9PcSQsYSwFq5AqxCEVHlsnfMW1kfi4SPUhKQauTrBrjyLhX1Gng2C57Jxcun1CpGqmSCt6yKoqvMMBtS+tMaolEDdVxkN3bQPjtG4+LUvK+UwsrlExFYKhGh8uH3Xk9zGAaIapW0JzHlVqZ/5c4glHGAcVDGUf/xBVH1su/14PwE7sIyMGKQpqIQta+fehknwhiyO6/BvczMLqJaqdgMTlS9NLvcW4I01cmEzFpfyUMglN7rs5ZB0BegASaT1Do5QmZtA5QyMC8DK19AVL0aUuCZLKxc/sHnnUSoZcNb3UTraK+XKXSXVsGcx7FD+un5cAv++g70ijAbPNsZHniMgAzDqwxsZ1KV2nfzo1RRhNqXv3r3aHBxCuq48Ld2+4YcAACExBSPHwetNWS7hfr3T1BBAIDALs2Zvy3OU9Wy4K9tof79c8/mS0qJxvfPyO6+hp0rTOjM4+lakN0cOtNSIqyUzXqRkhJDGqQ9AKUkCOewsnlEjVrf7lMGrY4m1B1/lpQmDd4J0ABzA9e/fkDhzW8zG6QNZ3hmQkkBFQRonx5BK2XKF342FQ2+hZt6XlfHGyb7QZkJEjZ2oMLQaPx5GTDHuff7qqQElIQSpsxkPAaTE1BTbkpfTrEELRUIo+Z9mOI5Us4BzsdmjaWiCLVPv/d6GVXQRqVeReH1r2Duz39H1KgNbKJU0IZoNsCzeYhrMiR2aWFiRulamKGPqx4zjbB8Dmo78BZX+p6HhHN4q1vG7/KGDysAtI8PwD1/qi0oGnqoa4AMku8mkDI90iDtnihhDHAJIWB+Ft7KGlpHBz1tJWaP+BBWZkd1Ey0lVBTObP8WoRTMywwEEXahBMQEnlpriHod9W8fe8eiWgXO/BIyK+tpeXQIw9TIuecD2vQFdpv4ecZ/sHq5kgJh+cJYP3U2J878YqfMn5xrlTIGMAY84JS6wSiAxLUfRM364MS51midHiKzvvXToZNh0i+y2YBVmINsNaGVhFNagLeyNrEAV4Zh3xBAl/DiFO7cAgi9Kg8SQmBlc0P/FuMOM10tOkoZ7OLcQNUFAOxiqoGWMpw0SLsHSgq0Tw/RPr2a8mydHiG38xoybIO5mXtNtBHK4puaE7QojArlFrLbr9D48aVXjrPyRWTWNmPLPFpEfabcXYLzE7iLK2BpkBYLsayBzEe3iVo066h/+wTCOTKrm7DyhQeX2FQ0+DkF56ewcgXYCWuEfwgqCo3hdfUSoBTu/BLcxeXEBKLX5UH6jodBZ4Lw9u/nfg5h+bzvGHVcuEur5vWdl6CWYyYREzEMRRCXhaecg/u52O+wi6VEbO6sbG4wO1mcH1tWNeVuKBEB2mRgZ2FgIwl33cyhpewL0AAASqF9cgh/6yWYbY/8QCOcw11cQeuGKTVzvfhgpqMLFFYrkGEbdr70oNLVY8JsG9ntl70A9Gd9OHElC8DIRaQMQQPuwhJ0cQ5Rw/QmWbk8GvvfkVnbMF8iBBo/viD/6h1oJvugXxdeDmZ9AROocT+XqLLnfVEiQu3rx6sssFJonx4BIPCWVxORUbNyBbSO9geO2/ninQITO1dA23Z6pTjCLWQ3d1H/9umqPEcpcruvQen9RHzvA7MdEM4HJGOc+cWhfxdhDP7mLhp7X3uZM57x4c4vJ+KzotxCdmsXKooggza464FwKyHB79NHCQFRr6J1egxo00ZjF+cSuWZeJ7067sGw3gLRaoBZ1r0+dEIonNIcuu4FWkpY+SL81c3YUqeKQlQ//N4rCQSnx7BLC53G2uR9rHc+J0Jiy6MgwzWFUszwYf3bJzDHBfMyEM0GWscH3Vf7vrZ9eozM5sO8Zod9FoSxW3enxpJKdEpT2uhYcZ5IjUEtZWyvnxkMWkrGwm/ZcOaX+qZYmZeBXbyb4C61LORfvkNYuUBUr8GZX0Lr+KD/GacU6l8/milEOpkpRMI58i/eov79s+mZIwROacHIygx53yljsPJFFN/9DTIIzHXFeaIWYcrN+sC9zLRPJRYlBLRWZrCFMdNnOsH3r09EuTNENY7JXK0UgvJ5XxKkefADotUcWtVJCsk9swQzTLuKOR5A7v/gptyCO78EpzjfORA/Tq+kROv4YKBnIyyfdUoxs/uxmgm4bVQ//dk3CZVZ2zA+h0oZJfEZ/hsfBcpgl+YRXpz1NYJb+eLg1KfWcRqvI2EVSsDR/sC0mnujqfvm7xXNBmpf/rrWI0SQ3X0FK5tPXulhSB/TfXw7HwvKObzlNbgLS2YYxHFBLXukHlZqWXDml+DMLUJLgXpMb5eWEkpK0Amt14QQMNdD7sUbc88Tcqehj24P4r0Eh585SgqoMIBoNRFVywBlcOYWwBxvIgbvXSWA+rdPvWqKSTw8XKZGS4H2ycHA8bB8Dm95faKyMqOSrnT3gDAOuziH8PLi2kFiIvIHBg93kmBQCqJRj31Jtprg7nQkBsYFcz0U3v6GqFqGlhI8m0NUq6K5b3qg3MUVuIsraaB2DcoYMsvroIwjuDiF1hpOaQF2sYT61499X+vOLz04K0k5R/7VWzT2vkG2msYXc23L2FgNQYsIjR9fbgQ/Go0fX1F4/f7RtaJ6AwB33J0TxkC4NeAIYBWKAE1OQDmOidGuFpyW5vkW17Q/jcxhkrJgTx0tjftIcHHWOxZVyvC3XoCwwqNXMrQUqH7+00yjdwjLZ2CuC3dh+cGbuGHi1oNe3MkiXeXuAeUcmbVN2IUSgvK5yYAtLk9u90bNLjOu7HqXsfuk0w1U7eIcwmoF9S8f+/rR2qdHRgE+DdL6oJbVyaosw3TG0t60MYCOzdQa2BhKLYRScM9Hbvd1J+giP23ENQbvg/2GumcZ9jh0f2/raB+iUQd1XGRWN8Ac99bAg3ALud3XqH39AN2ZoGQZH37CyyMPgTAOd2kFrcO9vuPczyaivJvyiCjdF6B1aR3tm2nwRw7SRLvdF6B1Cc5P4RTnQR6icDCkjSZp09pxPM0nzQSg3IJdKIHn8iAdP8qJ/W7GkVlZR6VW6ctKcD8382n+rm9gY++bUci/PI8dGIgatScRkI6bm5lYO1+E5WdNyYiOXydslEwHIaQzwXzj8yT3E/C9K1pEff2bKgpR/fg7Cm9+vTX71C25FV790nOBML6zTyO7o5Uyfxchvaw0obRjIE/RPjuClgp2cc54yD6RvzslnmGDWSYZ8PiZ46H7uzG0QdDOQEz10x9XGTVC4G/tgiR8w5Xss5sBptXwTG0Hhbe/oX16DBUGsAslI60w4w9SLaKeUTL3s6CWHdu8zW4pq6UYtNYmQ0UZ2E+Cd/O1EuQRAybCONzltYEJZndp5VF36WGtOli+0xqtkyP467cbrRNCzA5+RnUKh6GiCK3TI0TVMii34C2vg2V80E6juDO/aLQM0Sn7JjzbkPJwCLdMQHSjF5N5GZAJlPeZ44IwNlCWdOeX7iVpdRPquCi8+RWi1YLWEpaXNdn/hF/baZA2oxBKexYwWusnM/ko2q3eghqWz+Fv7gwIQFLbAZvxvrvHRokIYaWM8PIChFsmE2I7sdeJiiIE5TNEtSqY48JdWgHl1tgfXt0sDXddtE+PoaHhLiyDZ7IDmx0lBLQUEK1mpxn+flPTwPBpbBWF0FqB/ExM7Ilx0wpKhSFqX/7qs0/qBacpE8VoeOnpOGMQILO22ev9Ncco/I3tiWz+CbeQe/kOjd5EL4W7sGR07saQTTPXtA17xqpNaZA24xBKJ5CInhzXd1EqChGUz5HbfYP22TFkGMDOFTr9f+kCMgwlItS/f+kTzYwqZeRevgP1+/XRVBSh+vnPniiqaNQQXJ6bUuAjZCsp56C5ApjnAwTx08tCoHW832cGz/0sslsv7/W524US2ieHg8eLpYnZHCUJJaJYP93W0T64l5n5bPwsoqSAqNfROt6HikJYuQK8lY2xT1WazY+EaDZAbQvMNhsgJQQaP76C+1nkX71HVLsEKDNT1xO6Hggh4K6H3O4baK0AQowEyDO8R6+TBmkpiYJnsjD9DyblHpbPIeo1ZDZ2OsK+aenlZ3RFG2/SOvwBtvO6bypWtJqDqvVKmVLg2uajvde3TeaqMOgL0ABANOoIq5dGJ2vEXXWclhj3c0bwNWmyHxNgwEbq+vEp2yc9V0Sz0WeFF15eQDQbyL98N7YNqRICQfmsbyiEOi7yL95AAxD1KkS9iuD0GLzTx9o63Efh3W9j+f13Jd2A95MGaQnHNPeKjlYQTZA9y+NAOEN25yUa37/0GllZJgPueekO/44Mc2yQQTAwbi7b8cbsqt26GjaYMGGMvyEAhJVyx+JntOu/T0us3QKznQeVT2edYa0CVr746BN8KYMoEV0Tnr52PAwgw+DeQYuRnOm4vHAOreTA1K4K2midHMFbWukd00oO9UFNmTxPd7V/AiglIeo1NH586ZUB7flFZBJmYj1OKGWwsjkU3v4GJUVnWpE96cB03AybWOR+rs8HVitlDNjjvjaXm1rGkjnxZVZq2Wajcg/GoSX2VCCMIbOxjebet94x6jjILK8++9LSVNAYsL/qvSTis54/Q4UhGoc/EFUroJzBW90c+rVRrQJ3cQVWvjjQ/8v96T0HUgzpypdgtBADQqTh+Sm453fG5J9mqYZQZgKzhKe9e1lOqa4sTBIQTBLG4K2soXV0cO0YN5Zh17JQWkooJQceztR2jC7RlB7Opg/mhm8jIfCWhrsZpNwdyhjswhysbB6y1QThVi+7mDJ5CGOw8yW0z44GXmNDNlG3oaII1S9/9doYVKTQPPiB7NZu7NdTywahFP76NhqEIKoYX14rV5jY0EDKcKa/oqQMRdRrscfDi1PY+cLEGjpTBtFKIWrU0Pj+uZfltAol+OtbU3+oUcbhzC3BypcQ1Sqglg3Lzw2OsRNihCJL83DmFiAadTDHAbUdKBFNLetEuIX8q/doHR90zsmFt7oxMxqA3clUGbTBbBeET9b/8C507ZNSKZvpQyiFu7iMqFGDbDU6Bwn8jZ2hZvK3oUQ00GeqRQStNZjrDQyNeCvrvc1ldmMHem2ze2KJ2HQ+d9JPIMkMyxoQikmIC6YMp5flvNZoHVXKCDL+WCxMHgrtmEvfZhFmerVWUfv0J6hlg7kuoloFWkrkX72f4Nn2Qwgx8jJrWyPZOCUBJSI0jw4QXlwNPiQleI+jJ2iLyeqhKSk74sZpZhQwzfK53VdQIoIWwmyQ7inDMUyUtnW4h9zOa7TPTxBWL41Dycq68ZzuQDqm6inJYTaefE8MrRS0EIhadRBCwb1Mx1Kn/4Fl+VkTqKlBE+t0hzNdolYjdhIuvDh7uIXJBGGuh+zuG2OZ1Gqa0f/l9USUvrrZnllCBu2+AA0wwbsozvXEYZOCiiK0T48QlM8BQuAuLMGZW3jUYFKJCKLZQHBxCkK5kdMZot/3/7d3ZzGSrNldwP/niyX3zNr3rbu6uu/te20ZuWXZEmaQZgbslzEPFouMmZEMfhghZCwsRjJP+GUwjIYHA2JkJA+8AGMJeQRmYHzBFg+MxUggJOOZ22t1VXd1VVd1LblnRHyHhy8yq7Iys2vLJbLy/KSr7orMW/1VRlTE+bZzhoH2vTClScXsPrfta39+yu7OZhbLjZmO/LlNQlYyDdjWaem4M5UmRHTJGeozZoZfKiL//NPGQ56Uhcz6A9jnaiqSbSO7/gGKW88RVMogy0ZibsHUURMD1XEEQFlDNcipLBtuJgs7kQAzm7WAQ/rAjILa0bu2x6tH7+BkcpEZOdK+j+Krzaa1iOU3r6B9H4m5ha5tIKjn5dJ+Dcpx4ZcKKL583ni9dnTQlER3mGjPa/kMozBqSpaFzNo95DefNDr4ViLVtDEkKtehuJgEaX3GvofCy2dNozCsAxS3niNz537TCEZ9lC1z9z6gGaDBF4TVngevmIdfOIGdSsNJ5yIx6tJvdjwJsuyWckOJ6dlITmtdZBjbHEXK6bwzNUrBO2vdspMPMMWsE9OzprNxQ9r3UHz1srEQHQDiM/NIzC2h/OY0FUTp9Rbsu8mhu4/4pULLZ+gdHyKYmIbKDDBIUxbsVBpjDz6G9jyzESuC6yLF5QzkaU9EE0T0XSJ6HP7ZcR6AiLJE9IqIfqufbewVM9XZuq06qJRNluU2lO1AuW5jF86g1MvJFF8+Q/XdPopbL0y2+g7JMW+z+iinSb5rgufEwjLsdHbALROD5I5NtFYxCKcSr5s+pCdYg2yndTMGa3Qrna1XyDcFaABQ2dsxyzvOrDFsSaY8BFhr1M79bHXVowPwgJMCk1JQjgs7mYIVj0uANsQGddf4CoBPmHkDwCfh1538BoA/6kur+kG1X/RPyhr4YvOLeMV8y84gXa2gdtL+ZnWbERGseBzptXWMffijyN3/CPGJaVnjMeKUYyO78aGZ2rQd2OksshsPI3VdMLOpybi4gsTcIjLrH5hEtjAVP7pxH9KBj9q7/baveYWTpiUb9RJhQ4UIqsPOWCsWj/y9XAyPQd05fg7Anw///k0Afwjg759/ExH9OIBZAN8B8KhPbespUgqxiSlUzy0ujs/MXTmTer95+dZSQ4DpMcfGp0ZynYP0UIeT1oHZvHNiMqs72VxXisoTKVixOFIrd8E6AEUwjYGuVXHy9AeneeiUQnrlLkCE5Nxid65potaUL/WXLPt0ByIppJaiufP1fYgIsYkpVPZ3mzZ2kbLgjk0OsGXithnU3WOWmXcAgJl3iGjm/BvIzA18DcAvAvhsn9vXMypc/G/FEyZQI4XYxCSU40J7NSg3FtlemJNKo3bY2jt2kikgom0W4jxmhl8soPD8Ceo1YrFDyNzZMBnWu3AtR3VnqvY9U8HkbKJgrVHcfoHsvYddK+itlIX4zHzLRgoTxIyDdQA3Ow4nNx65IPaylO0gt/EQpZ1tBJUyrETSBLlDtrZORFvPfjuI6A8AzLV56dcv+S2+DOD3mXnropsmEf0ygF8GgJWVlas0cyDIsqFcF7GJaYDZFNMtFkC2g9zGh6CIJu10MjmT6LRWbRxTjmvW4UiQJoYE+x6KWy+As6uvmFHceo7svYdDkz7lWsLd5S2Hfb8lZcNNKcdFZv0BSq+3EFQrsJMppBZWoBwXybnFrv5bg0AqHDVdXjMbu5SSndGi63oWpDHz5zq9RkS7RDQfjqLNA9hr87afAvDTRPRlAGkALhEVmLll/RozfwPANwDg0aNHg12xeQns+yjvbCNokxXaFNSNZpCmHAfZ9Q9QOz4060pSacTGJiLbXtE72jPXqq5VYSdTpuMxJCMirLnt5h3teR0379yEDnzzEAcPfHc2YEaz2iY87fLGBmVZUKkMMmsbAPjaGewbeSWLeYAITiodic+xTlk2cM3YjJkbo5omV6Z0dkWzQd1Vvw3giwC+Gv75e+ffwMy/UP87EX0JwKN2AdpwYrBu/zBgHe0YUzkOYpPTiE1MmXUnclMZOfVdvmc3kcSn54YmyTIpapskGkp1/XrWXg3F11vwjo8ARYhNTCMxMzewNVhk2YhPz6G8+6rpuJMb71nQc5PpP5NXsoD888enaYtIIbv+YOjzRWrfQ+34CNUDM0YRm5iGOzY+dOvzRG8NqivyVQCfJ6LHAD4ffg0iekREvz2gNvUNWTbc8TaLS0nBjg+mXuJV1Mu5SIDWH8wM7XnQXq1jcN+3tmiNysFeyy7fyts3zeucukwHvhnp6sLPT5aNxMx8y/HE7EJXN+9o30Nh81mYhoIBrVHd30V5bwe6Q+meXiOlEJucQnJpFVYsDuW6SMwuhAlY7ca1FtSq0bjefB+Fl8+bq3uwRmHr2VCn/tFBgMrbXZRebSKolBFUyii9fmmujWAw14aIpoF0e5n5AG02AzDz9wH8zTbHfwfA7/S8YX1CSiE+NYOgUm4kQyTLRnp1/VbUTTP1AOs7xySD/U1o30ft5BCVt2YXmTs+ifjUzMB626wDePnjtq95xTysLncydOAjqFRQ3n0F9n042XHEJ6dvNDpjdlhPw4onUd3fBQDEp2dhJVKN0aT6NayDwHRIlHXlUULWGn6lhMT8EpxUOgx4CJWDPSAIupIw9jqU7SA2PgU3M4azU7A6COCXCihtb0J7NZBlI7mwbHa+DmjnOeug/dR0tdqTqem+0YHZGXqOSSY8F8lNJ2Iwoj83cUsp20Fqac3cuLUGWSpS6yyuS/seyntvzM5VZrhjE0jOLUVix9Np8EhDsciXtUb13VuU35xOTVX2dhBUykgtrQ1mapFMksygXGp5yeqQN+omgnIJ+Wefnn5dKcMrHCOzdu9GgaqybbjZHOyUmTI7G4Sw1vCKeRQ3nzXWbjmZHFLLa1f7N5mRWV1H9d0+yjsmwz4pC8mFZXDXUsZeDxG1bJBg30Ph+ePTrwM/3EzxIVSy+9eaKRnlwy8VodwYLDfWdJ/Q9ZFZotY6uUM+ks/MbWv/gjnyS15Ef0mQNkDDsH7nKnQQoPzmdVMOuNrhAbRXQ3plfaA/r/Y9VA/eorK/Cw4CONkxs9PsXMoB7fvmwRzWsRzkYl4OfFTevmk57p0chcFD/z9PZZkCzefL4Sg3Biue6Oq/pX0PpZ3tluNBqQjteV0ZTWw3QsSBj8KLJ00PUS9/jEo4ynHpjpSy4JeKTZnpWQcobr9A7oMfuXHbu63aoe5oZX8XqaW1rnYgtW+u7bPXtxVPNJXG88tF+IUTk1fyoDmvZGJmPvJ5Jd+HSEHFYtDVatNx5caGvqMuumt4r3IRPTpAtU0eNb+QH1hQAdRHpPZR3n3dOOadHCFfqyJz937jYa89D4WXT+EXCwDMguf02gaseGKAgVqH9Sl9LjujgwDQARgA2Q6yGx+h/GYbQa0KN5NDfHq266OlZn1UrX172kyBdYtfLrX9fGuHB4hPTF/pIdqpdJBfLPRk5PFGOl1TPbjW2PdaOiBBpWwC4Zk5sA4aO+DTK3dhxeJhzjVCbGoGTjo71MGMchykV9Zx8vQHpxtYwqTCnZIADwvWuuubyswsiLkXklK3YlnQZQ331TDCtO9B12om/1AiaerwReGXu483+svicJHueUGlbBa72w50EKD0ZrsRoAH1XYyPkdvoTe4ss/DZfC5kO603NVKwU+mmNgHo+7S49jyUdrZQOzIL4J10FqmlNaRW7oZT9VZP2kPKgpPOtiREBQAr1t1Ru/P/bvvjV/sZzQabDt8rgg+Z2NgkKns7rcenZrp+fr1ivv3x/BHiUyZ/pPY8gBmFzaewUxk4uXGAzbR6JO51F9DhutxO6/msWBxjDz6GXykDDNiJhPndHtJpXO15qOWP4eWPYSeSiI1Ptr+vXfX7+j6qhweovN0B+2YWJLmw3LXEy1EX/StdtNCeh8LmU/il04e3OzFl1n4N8uZFCnY6A7/QfAM2Q/iDfSh1THlSDx61bhsMsO9BB35XR4lYawTVCorbmwjKRZPcc2EZdjrTdENXto3U0vd+S34AABSZSURBVBpOnv7wdPE0KbPBpE/nuR68nv1svMIJ8i+fmnVhPVxrqCwLibkl+MVC04hacmGlp0GOFYuDbKdlwXp8Zv5KP6+ybcRn5szU6RlkWbATya60tZvIcZBavoPS65dm1IKUqY7Sg4C4U91L5bgmXxsBTuY0QPeLefjFPABCLIJTxWdp30dQLpkdz8yITU7DSWdapufNhhQX7i3IM3k+LY93fIjK/u6Nq1hwmOy9vLPVOOadHCJfLSN790Ek1jr3mgRpQ4aZUTs5bArQAKD2bn/gBb7rQUXhxZPGL6tyXGTW7g10CJ8BuLmx1hI1lt3ULlKq7fRit3u2HPg4efKDRoZ37dVQ2HzadoG2cmPIbXyIoFYDtIYVj4e97T6NpOmgbfAalIp9Sc9guS6y9z5EUClD+x7sVBpk9XbHMNk2susPUHy1Cb+QB9k2EjMLcNLZK38vO5lGcmkV5Tevwb4HO5lGamkVFMFcWMqy4ObG4aQzYK3DaaXejNra8WRL9RIASMwtNs5tYm6xNUBfXIn0zkfWGrXjQ5RebTaO+cU84lOziM8uRH6zkkm/UkFQLofXu8lTp9wYrFiiY1Dkl4staXnY91E92DOpba55DbHffl2urlagfU+CNBE9rAPUjo/avlY7ORp4gkfLjSFz5/7p4nvL6sqQ942wRnxyBrpWawS3ZNtILd8BYNpFloXY5EzLdI8VT3R9FLB2cty2BE95bwep5TtNN3KzC88dbFWHjlPY/fnnleP09WZMRLBicaRX1sPzRCDbulRgzGwSVddzCSrbbkp3cd2s+/1SH93pNVO95AEqb3dRyx/DcmMmQDsz6mK5MROgV8vQXj1AtyMd6HDgN+3Grqsc7CE2NRvpANPk9TMzNIm5RVTevW2kqAEAFYsje/d+23tRu1JjgAne6gH/9XD76hjoPDty20T3biHaIlItOxLrrFg0EuGaB2p0ejisNfKbT5GcW0Ryfinc/q5R3nuD9ModAKe568Bs8lhpDSeTQ3JxtfsL4nX7pK+s9UDX7rWlFJzsWMtuTisWH+qF25dx1WBKex5qJ4fwTo6gYnHEp8xmCiJ1u+uBXpNyXCTmFhGfnuuYEqffAfpNMeM0R2TLC9EOKrz8ienEKgU7mUb+2Q+bXtfVCir77UfGnFQazUUODTuZudl9wrLg5CZQe9e8uxdKyZo00V59lxuAgSRqJaWQmJ5D7fCg6YFOtnOt6ZhRoCwLYI3i9oum43Y621SvUNkOErMLJlgDwgdH939F3Ow4yjutve3YxFTkRlmUZSO1uIJCEIRrgszoYnp1fagenr2mPQ/5F49P88flT1B9t4/c/Y+it4szQszI3e0J9okIKhaHPleXuVeba7qlPk0LmA6YX24/MubljxGfmm35WaxEEnYy3bQMRzku4pNTN/q5lbKQnF2ArpRPZ0EsC+nVe0OdguUqRuOn7BLteyi9eY1amGbCzY0jOb/c94eVchzkNh6i9MZsUbeTGdO7idgDPipMNYd7Yf0/05tVjovU0mpLUNSP6R6ybSSXVlF6tdVojzthFhdHkXJcpFfvhiN9AFlK6gueE1TLrQl+tUZ5bwfJhWWoAW+cEf2hHAfp5TsmtcaZTnRq6U60gwoiWPGEycHo+x2XVyjHBVTr0hVlO0ivrcMvFuDlj2ElUnCzY115NppUSOvgIABrDWU7PQl6zfcf3ABMJxG+aqJFBz5KO9tmBCtUO3oHDgKzjqgLAZIOTAmU6tE7EAB3bMKk1jh3sZCyYMUTZk2V5qHInj9IpBTsZBJjH3yMoFoxJX4cd2AjQcqy4Y5NwM3kwrJDlgl8InwTl6Ds/YJyufNxrTuWgKpXwWDNIEVDUXXE1PRkBNWKmXKybFgyqtpgxRMYe/AjqBVOzLKJbC7y55WIEJuYRvVgLywJZrUdETQbO9rfp5TtwM2Nw82Nd719ynaAHt6DtFdD8dVLs6yDCLHxKSTmFiJx34vuUyFqtEbtsHWXm5c/7soCRmYNv5BHYfN0u3559zXSa/fgZHJtF94rywYkNrsUUlYjOIsCpSzTWxv8PeDW60cVCTuVbnvcSWc6bjzRgQ/v5LiR8oIsC8mFFTiZXOSmveuCWg3V/d2mupNOdgzJxVUJ1EKkFMh1EZ+YGnRTrkQ5DrIbD1He20Flfw/p1XXUDg/g5Y8b6wdV7PZN3ZsNE89Op2qZG1VzEvNLAx8AieadIILMyHWnRd2XW+ytAx8caIB1y8OCfb9lzRQAFLc3kdv4EBSR4EJcXT1ICMplKNeFsodrMfQw056H4tZzeIUTAOHU7dq9rleRUK7bssFCOS7i70kEW29bHQeBqZW58TCSQRqzhvaqLYXBvZMj+LlxWOOTA2qZ6AYiguXGkFxYNkmqlRWu0Z0FFEV6pP8mWOuWlFYAUD3cR2J2fuA7cm/np94DpNpnfzcpGi4exta+h9LrrUbOKbIdpFfvwk6kTH4uzW13BbHvnSZcFV3BHH7W1PtpYh34LUXSrWTqxgXCxcV0EKC0+7oRoAFmWqMXVSSU7SC1tIqgOgvv5BhWPAEnne0YjDMzqgd7bV+rHryFtbgSuczzHGh4ndL/HL2Dkx0b+KiDuLn6KH9dlKdpuyKCVXLOuuWffveoMK/W2SLSyo2ZXW4XPGzrtSPPJgVl30P+2ePTwEwR0OaXgSwrcjfrYaZ9D5X9XeSfP0Zx8ym8YqFRvqUX2G/NmxSUiqi+2wdHfEv+0NMataODlsPsez2p/alsB04qg+T8EmLjk7dvtJSoYxLeXkwhC9EPpKy2FTCcTK7tM7nfZCTtCpoStSI8uZe4EXMQoPqutfA4WMOvlOE6LpRlIzG3iPLrraa3JOaWor0raIho30Ph5bNG2aoApsRR+s4G3EyuJ//m2VGcs2rHh4hNTIHsy98EtA6AQAMUzYX8zGxqoRIiU4OQiNovRhhw24gIsckZVA/etrwWm5yOxGd3Xr0iQWVv51yCUUJ8eu72j7iIodW4N4EBUNNzm2wbmbUN5F88blTAsBIppBZXIzHFO/gWDJnrJmrtdNOtZzEnpRAbm4SdSKKyvwcCEJuaHYmkof3CQdBSVxQAyjvbsBPJngQ+yulQo9B2rhQoaK+G0u4O/PwRyDaLeE2bo/ErrH0P1cMDVN+9BYEQm5qFmxsfaPs6VZFQsVgkbr6qUStzCxz4IMs26TqivP7UtpG59wDlnVfwSwVYsYRZXD0iiUXF8Gls0NnZBvueyYywtNZYqmRy28WQXf/AdD4a1UKi0REe/J1qBJBtIzY9h9K5jQFk2bDO7JZRtg1lZ2CFxZclt1J3aa/9FJeu1Xq2/sBOJKEcp+XfTswtXDpQ0J6Hk2efnm6H9zwUnn+K9J37cDPdT2BsKjLwpTsHHAQt6WlKrzahvRoSM/MD62TUq0iw1mbEijXsdAappbVITEUqyz6tlclsSklFPFWDZVmAlURycRWAaXOkg0ox8oJKpWmDTlAp4+TpD5F78HGjaoEpv9c8AFNPj2OmLga3cUKCtD4gIrjZHHh2EZW3b8A6gJVMIb10p+0aj4uCs/rF44WbGJywpl2Ub+5RYDK/E87vxrXfkybhppTjILP+Icq7r+AXTqDcGBJzS1Du5Ut4aa/Wkq8IACq7r7o6msZamzV7B3vQtRpiYxOwU+kLe5RaB00BWqN9+7uIT073pRZkJ8p2kJhbQGJ61hyIWO3MftXK7LZRKclzE/UpNmZTyzVKCVJHhQ6CtgXawRpe/gjW5Ez7/8/3UN57Y1JxaDaJ6xeWBtIhic7d6pZTtoP49CxiE5MmRlB0reFUZoZfKSH/9NPTWnCkkLl7H3YyFcm1LJFhWUguLKP0+mXjENk2kvPLoB7ePC3XRXJhxSQ1JbpGTchah+MeOPChcfU6k22/X62K48d/2riuvONDONmxsDLDe67VTnkCtb7RzmRmbR5y9QLNlnWt0eXzu9WE6DXWGn6lhOLLZ2akngjxqVnEp2cjM402Epg75jHtdFzrAOW9HVT3T3df147fQXs1pNfu9b2TJ0FaH3Wj18y+j+Lms+ZivaxRfPkM2XsfSD6191CWBXd8Ak4mB694AmU7JgVKH37plGVdO99Offr7PCeTQ+XtLpTjIDY5c6Obhw6nLM8XgfZOjqD9xfc+WEiZAuJ8bkrX5CK73uiuDmuFFrdfhJsRFBIzczf+OYXoBw785o40Mypv30DF4oiNT0pnuk+UbSM+OY1Cmw1cbnas/f8UBKgetG7080uFcMNMf+8/Mj82ZExCydaRFe3VJJ/aJahwHWB8YrpRWy7qN0yyTK3Ps6x4ArHxSVSPDlDefX1ut9016ABBpUNpozZTrU3tsx2kV9ebtquTZSG1cvfaa7848FF48STckQWANcq7r+GX2hd+FiJK/FKxpcMDANWDvbb5MEXv2Kk0YlOzpweUQmq5/VKjhk7pkQbwjJUu6ZAhIoBU60VEKvLBhrgek/pgAk46C7+QNzcX1ii8fNaYagwq5XDN3bX/EViJVNsOgH0mN2A7RAQ7nsTYg4/hV8omc3ks/v6b4AXOZu4/q7q/CzuVisTuTCFE9CnbQWJ2HompWbN0wlLvX8OtlJltyR83H3bdnq1dfh+50w0by0J8erYlrUB8ekbW3dxiyrKgmVHLH8Mv5Ft64zdd0KosC8n5RZwUTppG5dyxyUvl6atP5btdm27v0OGQjogYAnYyZUaWz617ik3OSN7LAbhKnWtl2UgtriK/+QRBuWSOOS4yaxt9WRpznlwtQ0YpC/GpGVixOCoHewAD8akZOJms7By65ZRtIz49i/zxYdNxO5nuSkoJ5caQe/ARqkfvoKtVuGMTsOLxgawBc7I5YIdaphfiU7MyiiYijywb2bsPUHj5zCRIDTcOuNkxmfEYAsp1kbmzAQ5OE9cPqqqG3O2GkLIdxMYnTdkKdGdnnxgOViyB7MZDsw7N9+DmxuGOT3Zlx5jJFeQiMT3XhZbejLIdZO7cR3HrObRXAykL8bmFjpsohIgSUgpWImkSpEoKjqGkbAeIwE5ceboPMQnORo+yLKhEEqnlOwDryJRf6jZSCnYqjey9D4Ym0asQZ50mSBXi+uQpL8QQMj3y290rr4/sCSHEqJJuqRBCCCFEBEmQJoQQQggRQRKkCSGEEEJEkARpQgghhBARJEGaEEIIIUQESZAmhBBCCBFBEqQJIYQQQkSQBGlCCCGEEBEkQZoQQgghRARJkCaEEEIIEUHEzINuQ1cR0VsAm4NuxxCZArA/6EaIFnJeoknOSzTJeYkmOS+Xs8rM0+1euHVBmrgaIvo+Mz8adDtEMzkv0STnJZrkvESTnJebk+lOIYQQQogIkiBNCCGEECKCJEgT3xh0A0Rbcl6iSc5LNMl5iSY5Lzcka9KEEEIIISJIRtKEEEIIISJIgrQRQ0QTRPRdInoc/jn+nvdmiegVEf1WP9s4ii5zXojox4jofxLRnxDR/yWivzKIto4CIvoZIvohET0hoq+0eT1GRP8ufP2PiWit/60cPZc4L79KRP8v/P34hIhWB9HOUXLROTnzvp8nIiYi2e15BRKkjZ6vAPiEmTcAfBJ+3clvAPijvrRKXOa8lAD8DWb+CMDPAPinRDTWxzaOBCKyAPwzAD8L4CGAv0ZED8+97ZcAHDLzPQBfB/CP+tvK0XPJ8/K/ATxi5h8F8LsAfrO/rRwtlzwnIKIMgL8D4I/728LhJ0Ha6Pk5AN8M//5NAH+p3ZuI6McBzAL4r31q16i78Lww86fM/Dj8+2sAewDaJkAUN/ITAJ4w8zNmrgH4tzDn56yz5+t3AXyWiKiPbRxFF54XZv7vzFwKv/wegKU+t3HUXOZ3BTAd/t8EUOln424DCdJGzywz7wBA+OfM+TcQkQLwNQC/1ue2jbILz8tZRPQTAFwAT/vQtlGzCGDrzNfb4bG272FmH8AxgMm+tG50Xea8nPVLAP5zT1skLjwnRPRnACwz83/sZ8NuC3vQDRDdR0R/AGCuzUu/fslv8WUAv8/MWzI40D1dOC/17zMP4N8A+CIz6260TTRpd9Gf3wZ/mfeI7rr0Z05Efx3AIwCf6WmLxHvPSdjh/zqAL/WrQbeNBGm3EDN/rtNrRLRLRPPMvBM+7PfavO2nAPw0EX0ZQBqAS0QFZn7f+jVxgS6cFxBRFsB/AvAPmPl7PWrqqNsGsHzm6yUArzu8Z5uIbAA5AO/607yRdZnzAiL6HEzH5zPMXO1T20bVReckA+BjAH8YdvjnAHybiL7AzN/vWyuHmEx3jp5vA/hi+PcvAvi9829g5l9g5hVmXgPw9wD8awnQeu7C80JELoD/AHM+vtXHto2a/wVgg4juhJ/5X4U5P2edPV8/D+C/sSSd7LULz0s4tfYvAXyBmdt2dERXvfecMPMxM08x81r4PPkezLmRAO2SJEgbPV8F8Hkiegzg8+HXIKJHRPTbA23ZaLvMefnLAP4cgC8R0f8J//uxwTT39grXmP1tAP8FwJ8C+PfM/CdE9A+J6Avh2/4VgEkiegLgV/H+XdKiCy55Xv4xzOj/t8Lfj/PBteiiS54TcQNScUAIIYQQIoJkJE0IIYQQIoIkSBNCCCGEiCAJ0oQQQgghIkiCNCGEEEKICJIgTQghhBAigiRIE0KIM4homYieE9FE+PV4+PUqEX2HiI6ISErcCCF6ToI0IYQ4g5m3APwLhLnqwj+/wcybMHm4fnFQbRNCjBYJ0oQQotXXAfwkEf0KgD8L4GsAwMyfAMgPsmFCiNEhtTuFEOIcZvaI6NcAfAfAX2Dm2qDbJIQYPTKSJoQQ7f0sgB2YAtFCCNF3EqQJIcQ5YU3UzwP4SQB/l4jmB9wkIcQIkiBNCCHOICKC2TjwK8z8EmazwD8ZbKuEEKNIgjQhhGj2twC8ZObvhl//cwAfENFniOh/APgWgM8S0TYR/cWBtVIIcesRMw+6DUIIIYQQ4hwZSRNCCCGEiCAJ0oQQQgghIkiCNCGEEEKICJIgTQghhBAigiRIE0IIIYSIIAnShBBCCCEiSII0IYQQQogIkiBNCCGEECKC/j8DGdwLjGTuiQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "preds = svc.predict(data.drop('y',axis=1))\n",
    "data['preds'] = preds\n",
    "\n",
    "plt.figure(figsize = (10,6))\n",
    "sns.scatterplot(x = 'X1',y = 'X2',hue = 'preds',data =data,s = 50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Well, its predicting everything to 1 class\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (h) Fit a SVM using a non-linear kernel to the data. Obtain a class prediction for each training observation. Plot the observations, colored according to the predicted class labels.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop('preds',axis=1,inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=10, error_score='raise-deprecating',\n",
       "             estimator=SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
       "                           decision_function_shape='ovr', degree=3,\n",
       "                           gamma='auto_deprecated', kernel='rbf', max_iter=-1,\n",
       "                           probability=False, random_state=None, shrinking=True,\n",
       "                           tol=0.001, verbose=False),\n",
       "             iid='warn', n_jobs=None, param_grid={'C': [0.1, 1, 10, 100, 1000]},\n",
       "             pre_dispatch='2*n_jobs', refit=True, return_train_score=False,\n",
       "             scoring=None, verbose=0)"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#lets use grid search to select the optimal hyperparamters\n",
    "search = GridSearchCV(SVC(kernel = 'rbf'),param_grid={'C':[0.1,1,10,100,1000]},cv = 10)\n",
    "search.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'C': 100}"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "search.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training score  0.988\n",
      "Testing Score  0.976\n"
     ]
    }
   ],
   "source": [
    "best_model = search.best_estimator_\n",
    "print('Training score ',best_model.score(X_train,y_train))\n",
    "print('Testing Score ',best_model.score(X_test,y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.5, 0.5)"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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YTxSdz+C5a6qjoJAQN4DoKO3m5i36aCMx5LNst8pr2wpQHUfIzc+nVryDIrKoHgOLP93IfTcNNNW7pcU3Pgo08vq9IXDc6/ckoAOw7rfVuOsCKxRFuaGqJPnyCW/Dbr2davHFJpd4tZJjixeZTo51cEl9R4XcLb2IiXYRE+0ikRjuu6Y9c1a9S+0uV+FyRREdG0dMdMUCbJURbmdm5QZcNormIK+7OUjhKrE7F04fQS3ykJ95ksJjP1K9WjI1kvVbHPrzey4iNdGFO7uQvvNO8uCltRjdPZFhbx5hzuA4hi8z37ulhdjaArRUFKUpcAy4BShNYFJV9SyQWvK7oijrgL8FMhuxpBR/ScLbtzv2c9NvSXQ7DxwnPbOA9b+eLfOZGpnHDRFb3sTHRnH/tR3Y/PNWVBR+PXWOs3XaQ90OhtkgG3CJXSk/kChZn07PMHko3lYrD3gkEi1ISEhk1wu3EO1QcTqdOBSIi4ujVnKsLufztVxPDPks2HyOOd+eZWgL8KhFDGziYPma76wttlRVLVQUZQKwiuLSD6+pqrpLUZRpwFZVVVeEclxfC0y++vNBruzRipT4GCbfNThc0wOistIS3sRGR9GvY2MA+nWAD77Zx9f7DtG2jzF2SiR27ezLixt/IXMtCcXrJwc89sKu75NeqKpK/96XMKpTXwZ0amLIOX0t1+OKTaRp9eoU5GYz6ZokUhNdTKpVyPYlWZw5e960UKImgVNVVT8GPi63bYqffQcEckxfirVF9mm+/OFXhlzWGsVXppgO+Cst4Q9VhTzVyVUd6pB9fD073voagLSCOPrc+RgOmbQu0YlI6exlJygxgkh5n0IlKzOd957/OyMefoGE5Gp8/fa/GNcjhd7tG1X9YY3wt1zP9Hc+g2PfkZrooqCwiMzMDK5tFmVqGQhhK8j7VKxRGfTpF0ffzs3wnZevLdkX8vjhl2PccWlt3tt5jO4XtybRx2KYZVFxFmaR4EnnzkG/hxF3HzrFUwsfp9+YqThdwl52iUR4ZCcoCQQpyvVlyyfv4zq1k00fvYsrL4MH+qTSs21Ds80CyuqHc+dzuXAhl7i4WNqcNm+BamF7/UoXmMw7ZogNr737GcnHvqNNwxSSD5xlyeLjId+odo3rMPUGhWnzHiE+uTp5+QW0vmY0tRo00dZoCyIbRXOQ111iZ+woykWZuX10/898uWw+Q1pH87+l83j7iTHCCC34XT+4M7MZ9vArzBlSh/Erc3h9ymjTbBJWbJmNr5yxYUvCK47WqlFt3v7z5QAUFHp4YN7LFF07gToXtdDMbitix0bRCsjrLpFYCxFmEKenHeeTlyfy4KXxPDKwGq2/PMsPe/ZzedfmhtkQKOUn2WkdRgxm4WsptvzgK2dsSAuHZjcryuVk5j2X8+D8WRxt2A2nK4rE1Pq06No37GNLJJLwkF4/ieR3fv1xE5nHfwW1iIzdXxJXkM6YS4qXvdPCEVFCMOIlkGNp7TApTzALX0ux5QdfOWMA9U9pF/N1uZzMvPdyfj2RDnjYsHsD367cT9chozQ5vkQiCQ3p9ZNIitm19gNa5v7ImK7Fs+2Xn3HRXXXq4ogIRrwEciw9HSbl64DeOaQ3NSvZP+LFlj8lXWnOmIY4HA6aNSguQ9asQSpJX//MJx/Op1XfoQAkplTHFRVcgVSJRCKRSELBU1hIVuYZAA5u+ZwesUcYdX230r9v2L5PF0eET/EShgdKb4eJzxDltf73t6XYCsYVqaWS1oIbe7emzq4jfL95Hqqqsn7/WXqPnUZsfGJQxxElkVIikUgk1qAgP4/1C6bQu3E8DofCjY1qcEWXjmX20csRoXV+lZ4OE38hyocUpaaqqmd8fcaWYitQAaW1ktaK3u0bldYquSUjiwcXTuayMdOCWntRhERKiUQikWiHnrmE+Xm5bFg4heeHd+SiujXCPl4wGJFfpSX+QpTb9jEOeMbXZ2wntoIRUHrPVNCCWtWTmDX2Mqa+Nw1HVAxZOXnU630TjTv0NNs0iUQi8Yv0rmuPXtctL/cCXy2czIu3daFBrWq6nKMy9M6vCpfy0TJ/IUrgCiJFbAUqoKykpGskJ/DquAFA8ZIITyz+Dwc9hTTt1Duo45w8coAMdxqTRpVdH0o2fhKJRGsi1btuNZGZm3Oer/89hZdHdqduzWRTbDBiQlo4lI+W+Q1R9npgkL9j2EpsBSOgRFfS/lAUham39eHp9z/l6+/X4nA4iKpWh27X34VSxRpGHo+HqMQaFRpAuzd+EolEYhRWEJlHftrG4U2f4FAU8s+mMWPUpdSqbl5ZE6MmpIWCVulGlhRb/hLggxFQoivpqnhs+KWlP3+z5yiz33yWvnf+o0rBJZHogdGjeat5DyQSUTj04ybU7R/w+l19ZX8RAFqlGwkrtiqbUVji0pu9bC0//HK0yjiqLwElspIOlsvaNsTlUHhp4RPUbt8LgLjY2AojqQx3GrGp4iypILEPRo/mreA9kJiHFOO/o6oqv2z7ioK8C1w466beuZ08PlIKrUDQMt1IWLHlb0aht0tv+OJvSIpSK8RRtaxCaxUuad2AF2smcty9H1WFzA4NaDf8UarXqlu6z6RRQ2g29kUTrZRIqkb0jlJ0+yRSjJegqipfv/08Q5urNK6dTFR9Jx2b95ZCK0C0TDcSVmz5i5GWfPlmNaIY1KiA6Jg4Vq6vuI9ItbOMol5qCvVSUwCY26we4+c+Q8uhfyGlVj35ckksg+gdpej2iYJc8sgcijweCgsLUFWVTe+9zH29a3CZQItEWwkt042EFVu+YqTeLr0zZ7O5q0s096w8z7n8HGYvW8vkMUOErZ1lNLExUcwdP5BXV/wbd14RZ7JycHjyZOMnkUgMIVK9fGaKzMwzaWx760na1Cs+18QBzenSom4Vn5L4Q8t0I2HF1siuCaX/l8RIS7xaKbEODrjP0yrVRa04KPQUsvjTjdx300BL1M4yipjoKP5+02Wlv3dpVpvv1VZ0HHRTpZ+TYZKqkddIDHYtfAhPbk7p7wXZ6UwaNUTeB52xy/Ovx/cw6/tnpJ1g95Jn+feEy4mPlUu8iYawYqt8jHT2srW89r+vqZ4Qzdxvz0JhPvFRcC63iDlD4njkizxeeHsVm7bvsUTtLDMYfVUnotbs4ps3J6M4HGR5ouh569+Jio4ps58Mk1SNvEZlMXo0X3K+XHcadW95qnS70+mkbqNmEXsfjMIuz7+VvocvYZh3/hyxFHDzDVcR7bnA3PEDiY2JMslCSWUIK7a6zyobIy1Ut9G0moMhV/b+LY7qJj3rAkPbFtGompOBTRy8+9lmHuydYrnaWUZy++Xtuf23n389mc4jC6bQf+w0omJiKv2cRFIZRo/mS843adQQGjRpaei5JeJjx3yx8sIwY+caYgrOkr3tI2aO7mGiZZJAEFZsbX1raunP7sxshj38CnOGFOdhLX3+L6iqyrCHX2HSNUmkJrqYVKuQj/cdYdEPF1i8M6/MsaxSO8tomtStwYsjOvLX2X8ntkZ9UBRa9fuD2WZJLIiW4RjRO0rR7ZMUi3Ffz2R2dhbPTBhhqVCnL9J/+Ix48mjU7XJ2bfvIbHMkASCs2PLGVx4WUGFK5j29akCDblJYBUHD2tVZ+verASgqKmLiwvkU5F0w2SqJ1dAyHCN6Ryi6fWZy9oy7wnJgYE4ul5VChMFwZtsnJEapNLy4n9mmSIJAeLHlr6hYTFwip9OtWwFeRBwOB9PHDuCN/64jY/cGXPHVcETFkNCgldmmSSQSE/DnsTx7xu1z/yK1yJYCx0wK8vL49eedFOTmkPb1UqpVS6JBh15mmyUJEuHFlr+iYjRoK0WVDjgcDlo2qs3RL+YBKgWFHvKLFGJTUmWYxAsZShIDeR/0xZ93aNszN/u87opaZIRZmiH685Ofl8uGBZO5o2dt3lJzadSiNcl1G5ttliQEhBdbVl/D0IpsmVu2tsjn3x9k8W4Plw570CSLxEOGksRA3gdzqFarLv98Y2WF7b5CiOGiZ5kJkZ+fvAs5fLVwMi/d0Y16qSk0qr2WI/97tcJ+qUlycpMVEF5s2WkNQ6tyRZemuJyHeGPxdHrdOlFWo5dIJIZh19wrXxz5aRuHVr9GnWoJKKi8OuoSalcv9rJtnnO/ydZJwkF4sSURgwEXNybadYS5bz1HnzsekYJLUgbRwzFWxi4FRI3Gas/koV1b8Hy/jDf+co1sX22IFFsaY+dFsHu1a4TL4eClV//Kpq3buOTSS+kx4mGSa6SabZrEZGSnrx9W8uyIJHBEfyZVVeX7FQvg3AkAGsQVMunOvlJo2RQptjTG6otgVyUWe7RpwCXf7eJUzDk6p5xn++JpdLxlEtVS65hgrUQi0ZNgxZPoAidctPIynss4w4w/38SrE4Zww5+6a2miRFCk2NIQOyyCXZVYLPsdv2fRU/cz+d2ncdZti6Io1GregaadeptgeXDI0Iz+yGtsfeR9Kks4XsaszDPsWbscVJUtaz+hZpGbfQcPQ682epgqEQwptjTE6otgByIWy3/HJas3s3DCFZw7nwvA4vVr2J3ppl3/oUGd2+iO2UqhGasir7H1EUEwixSaDJVz6W62v/MUz93Rg/MX8hnz2Snm31rHsoNySfBYRmxplQulV06Vv+KrVnqRqhKLgXzH+6/vysJV29n6cRb12hav11WnUTOcrsofNdkxS4xABPFgJUR4L7W6L2bd+0z3KX5872nm3NufhLgYpr/zGUNbOS07KJeEhmXElla5UHrlVPkrvmqVFykQIRXodxx7dSda7zzE0aMfUlDo4ZNPs+k3diquqGjDv5dWREonbffvKYJ4CBY7eHZEwIx7n552nJ+WPsfc8QOIi4m2xaBcEhqWEFta5ULpmVMVTPFVEWcsBiKkgvmOfTv+XuW4T/szPDp/Mv3vnkZUtDUL8Fmxkw6FSPmeVsIOIjcScZ84zL4PX2Tu+IHEREcB1h+US0LHEmIr3FyoEnHTuWVD3XKqgim+KuKMxUCEVKgFZpvVr8nzwzsw/Z3/w+mK4nRmDi2G3Eu9pvZNDLW7h0giiUR8eRkzT59EcbiYNGoIedlnIT8HFIXE2CgOvvcPoqN+72bliiiRi/BiSwu366KPNpJ+4jCL9x9mwz11Qz6OFog6Y1HvSv0X1a3By3cPAMDjKWLiwgWo/UdTv0UHXc/rD71DM9JDJMNfEvvha6A0adQQmo2dQfr3q4h3FtKoUx8Adi14qIzQArkiSiQjvNgK1+1aIm6eHBTPhBUZpQXjzHLfWn3GohY4nQ5eunsAjy16m83fJAKgFFwwtGOW3iX9kdfY+pglmK3gGS7Iz2PLkle5kHGKE5/No2b9xjTo2Mdss4RHxDQaIxBebIXrdi0RN3Xi8hjYxMElM45SIyku6ONogUyO/B2Hw8Gzo/qW/v6Hdkl8eDCKnjfdZ6JVYhBIR2OFzkhEpLctOMx6lvTwDGt57/PzctmwcAr/Gt6R9Z8n0/7qW0K2K9IQMY3GCIQXW+G4Xb3FTWpiCpOqF7J9SRZLn/+LKeLGqsmRRoxEBvdsQZTrAK8vfJIaF7UCFFr1upZ4QTpBIzvpQDoavcKUdhcjUohGLuHe+5OHfuHkz9sAcP+0iZfu6E79WilamGZ5Au0jRE2jMQLhxVY4iCZurJocadRI5KpuzejSLIusnFxy8wt48rXJ9Bz9BAlJ5jdokdJJR8r3lFSO9JyW5ejP28n+5i0eurYjALUH9CEx3pozq/Ug0D4iktNobC22RBM3VkyONHokUqt6ErWqF3tR5tydwn0LptD+xr8SHRdPdHQs8UnJup1bS+zuIZLYGznBo7jqe5FahPvwXvhxBS+MGeBzkejUpBh2LXjI5/ZIINA+ItLTaGwttqwobkTDzJFItaR45t3TjzfXvIlaBPtOniW28w206DbAkPOHg5Gj/5NHDuDxeADIcKcxadQQIHK9EBLt8H624PfnS/RnKxzPnKqqfLtkBs2dJ0mOi6FTUiwjRvXzKbQANs+5XxObrUqgfYRokSajsbXYkoSHCCORpIRYJlzfvfT355at4ZfCAlr2vNKQ81sBj8dDTOpFAEQl1ij1SESSF0KiD97PFvz+fOn9bIXrGQ7VM6eqKhsXT+fOTrEM7N1Gh5oAACAASURBVNw7MGMjmGD6CK0jTVab1SjFlsboufZiVcfV+twijkQeuakncz/ZzK631gOQSRKX3fZ3HA6HKfboQSAdjfc+Ge40ohJrAOCMjTfGSEnAyPyn4DHjuqiqyldvP8/dlyTSt0Pjqj8gCaqP0DrSFGousVkiTYotjdFz7cWqjqv1uUXLeSvh3ms7l/68ff8Jnl34BAPGTMHhdJpmk5YE0tF471NSVFGiH+EIJqPzn6S4C56ioiK+WvQc9/euwaVtG5ptjmUwq48IJ5fYrNITUmxpiF7J5IEcV4tzl1f8Vsh569S8Hv93nYMnZv2NxGq1KPSotLtmJDXrNTLbNEkQiC4QrJQwroWtJZ5Tb68p2MtzmnkmjR9XLsSpwPmz6fx9cGu6t6pvtlmWwqw+ItRcYjNLT0ixpSF6JZMHclwtzm3VYnPtm9RhycQ6AOQXFHL/3BdRh/6V1PoyFGAVjBIzoos6USi5Fnb1mmaknWD3kmeZc+8A4mOjzTZHEgTh5BKbOeFLii2N0CuZPJDjanFus4vNaRVHj45yMXv85Tww7yWOt7kCZ3QMCdVSadK2i4bWioUsMxE4VvJQiYBVny1fdhfkXSAmOoodGz7h/M5VzB0/kNiYKJMslIRKqLnEZk/4kmJLI/RKJg/kuFqc2+xic1p61aJcTmbecznb9x1BVWHL/o1sP7ybTlffppG1YiE9MpJAyDx9srQsiDeVefWs+myVt/vHtR/S+Nz39GtXD/iVi/sMrLBItMQahJonZvaEL/m0aYReiYKBHDfcc5ut+PXwqrlcTrq1KZ6y3r3tRbz/5R7WrXyDjleOAMAZFWWrGYwScRHFO6Qqjojx6qmqSmF+PgB71n9IV9cBRv+pp8lWSbQg1Dwxsyd8SbHlRTihLL0SBQM5brjnNlvxG+FVG96vLdW/O8DG/0wFYHdaAf3ufpKY2LjKPyiREJ5gMto75M9WhxIZg4uC/Dw2/HsqraqDosDVLeowpGcns82SmIzZE76k2PLCqgni4WKm4jfSq3ZVt2Zc1a0ZACfcZ/nL/En0GfsksfHiF8SzO6J4f/xhpXCaP1t9hRDtRkFeHusXTuG54R1oUrdG1R+QSAxCiq3fMDtB3EzMVPxmedXqpaYwY3QPprzzOK7YBHIu5NGg781c1LabbueU+McoMSO6qJMEz/EDuzm4+k0S42PJzznPiyM607B2dbPNkkjKIMXWb5idIB6pmOlVq109ibnjBwLFOR6TFi3hsMfDRR166HpeIxGx1IGZNpU/fokt2dlZZTw/shSENTi2dweZX73Ja+MHyBxMidBIsYX5CeKRTDheNS2XXVAUhX+O7MsTiz9k7ebPcDpdJNVuSOdrbvO7AK0VELHUgUg2iWSL3tjFq7fj86VkHtuPWlREPWcmL9090NLvqCQykGKLwEJZVlv00gjMviZzlq/j8IFfmL18LZPvCj8fRVEUpt7Wp/T39TsP89o7L9D7tr/Jxlxieezgqdu0dCY3tSzimms6mm2KRBIU0u9KcShr8c48us9KK/23eGce67btLd3HO3leUoz3NXFnZvOnf8zlzNnzhpzbnZnN8tXfMG1ANMs/+0aX8/bveBH39kxm/RtPs2/nVvbt3Mr5rLOan0cikfgmNye79N3b8PYL3NIGrune3GyzJJKg0cSzpSjKNcArgBNYqKrqs+X+PhEYCxQCp4G7VFU9pMW5taCqUFYkJ8/7o/w1OZ+Xb+hMzjnL1zGoUQEDm8Ux6OAFzbxb5bmsbUPqJMfyy7EvUVWVd15/i063/R8pNWtpfi5JYIiYhybRnvPnMtny5lTu6NUIRVFoenlNWl1U22yzJDbCyOhM2GJLURQnMAu4EjgKbFEUZYWqqru9dvse6K6qao6iKOOBfwHDwz23Ucjk+Yp4X5MBjXJY/tk3vH+rMWK0xKv1zg3RxLoc3NUlmttWfMN9fxqoy3mbNUilWYNUAPp1asa9c5+kw/DHqF6rrubnklQtpiIpzypSyco8w3dvPcnsu/uQkihr4Un0wchyT1p4tnoA+1RVPQCgKMp7wFCgVGypqrrWa/9vgds1OK8h2CV5XksFX/6aKEUFDGpUQPOaUYaUbSjxarVKjQegVaqLQY1ydPNueRMfG8288QN5dunLuAtUzp3PJa79lbTrK2YNIxGToquyyUgxJeL1iVR+2fw56VtXUCMpjmgnzLunH4nxMWabJbEpRkestBBbDYAjXr8fBSpbF2EM8ImvPyiKMg4YBzDv4eGMG9pbA/PCw+zq6lqhpYL3vibu7ELW7jvPjGtjcGdmGyJGl6/dRs65QtYf+t37cS5XJf7ENt3FFkBcTDRP3N639Pc5H33PrnWFtB/wB13OF07YTMSwmkg2iWRLJPPzN6uod3oj/3rwarNNkUQIRkestBBbvqZpqT53VJTbge5Af19/V1V1PjAfgI0zfB7DaMxeT0kLtFbw3tckPesCQ1sUL4uRlZNLy5rJmovR8l65i+rU4LhSVGaf5BioX9ucitHjB3fhtc92sOmN73E4HeQqcfS45a+4XFGaHF+GzSR2Zs9XH9H03FYeuNE+9e0kYmNGxEoLsXUUaOT1e0PgePmdFEW5ApgE9FdVNU+D8xqC2espaYHWCr7kmrgzs7lk1D9ZfyKWDR+XaO5iUaqlGC3vlfM+vyjlOO666mLu+u3nfUdPM3nBFPqNfQJXVLSpdkmMRSbvB8fudf+hVd6PjL+hu9mmSCIIMyJWWoitLUBLRVGaAseAW4BbvXdQFKULMA+4RlXVtIqHkOiFngp+0UcbaVrNwZAre1d4QEtKQYQrhCrzyom6lmWLhrV4+iYHj8z5BymNWgPQuPsV1Gkkp6xrgch5VtILWTmFhQVsX/Uenvwccs5mcPlFRYwZ3MVssyQRhhkRq7DFlqqqhYqiTABWUVz64TVVVXcpijIN2Kqq6grgeSARWPpbccjDqqreEO65JVWjl4KvKjQ5e9k6Nm3fy+xla5k8JvQ8Kn9eOdHLcTStV5O3JvTjfG4+qgpT351F0aBx1GvaxmzThKcqMSU9RNaksCCf9Qum8Njg5jSsVR2XsybJCXKmocR4zIhYaVJnS1XVj4GPy22b4vXzFVqcRxI8ein4ykKT7sxs3l21kebVYfGnG7nvptBKMlTmlbNCOY6Y6Chioovztl4ZN5CJCxdw7sxQklLr4XJFUbthE3MN1AitQ2dSTNmHrMx0sjLPgKqy++N/88zN7WlWv6bZZkkkhiOX67E5eih4d2Y2/12zmecHFFDoSaoQmpy9bB0xah7zb0hk+LLzIXu3/HnlZi1dy7rN20MKjZqV5+VwOJg+dgD/2biJ3MMeTmScZ8uWhlzyx3uq/KzIYTOQoTORMTOH7MTBnzi2ag7929UD4O5bO1G/Voqu55RIgsFSRU0lkceijzbSv0E+KS4P7sxsXDHxZGZkMnvZWsb/aQDvrtrIXR2jaJ3q5LaOUbwWonfLn1eusOg7RnaKDik0amael8Ph4MY+7Up//3jzPj5YOpOeN1cuiKWnRxIq/oTwtmduZtKoigMgrUTY8V92kv7lG8y57wocDrkqnERMrFbUVBJhrN68hx9/yeK/uxykX8jB5YqienQhy9d8h6pCjJrH6M6JAIzuHMM7O7ND8m7588rd8NBMFu90Bx0aFS3P67oeLYiJPsjKN/+Bw+HgxLlCeo78P+KTkk2zSRIeonshS1AVh+beyK3/WUDc2f04HQ5qJbp46e4BUmhJhMWKRU2FRaTSAHbiyh5tubJBDhP7pTBtdQYf7Mrh3VvrMX5lDku/2MoVTRyk5XhIy/EAMLCJg+VrvgsrUd6bUEOjIuZ5DerclEGdmwKQfu489y+cQs9RU0lIrmaqXZLQiFQv5OZls/hD0wIG39S36p0lEgGwYlFT3QlVNIlaGsDKVLVUz6IdDjacSmBDmekSLi6qa25SrBWWXaqRnMDccX2Y+Po0HAllC7Q6kuvQbehYfpvNK7EBotTkOnnkAB5P8cAow53G/YO7oyoOHIqDlJqpPu3Kyc7iu6WvEuNUyb1wnjsurcdV3VoaZrOkciLR0RDMd7ZqUVPdCUU0iRYysgtVLdWzcl8WS59/SLhrLcqyS1U1CCmJcfz7gUEVtn+96wjz3nqOPnc8YrjgqkoUWCV0JhqiTCzweDzEpF4EQFRiscivP+pl8tyHadDkdwFVYtf5rLNsev1xZo3tRY1ksd5zSTGR6GgI5jtbtaiprgQrmko6s84tGwoXMrIDRi/VoxWiLLsUaiPYu30jXE4HL82fQmqziwFo2n0gydVTq/hk+FQlCiI1dGYF/AlhhxJcLlXO8V/Izcrkh8+WkPnTRuaO60NKoqyRJSKR6GgI9jtbsqip3gQbV1300UbSTxxm8f7DbLinLiBmyMiqeOdLXfvnV/jgpyOsP+GkOA9W+6V6tEKEZZfCbQR7tmnArHrVyMw6j6dI5am3n6TjiMeollpHR6slVsafEH5mwohSEZbhTiv1aDlj4/Hk5pTZ99y+LRSd/ImUWAcTL86hwaABxMZos+6nRHtEzE3VA+8oQbDf2Yz+QOipIiWd08iuxR3SyK4JrFy/hTNnz1e6/5OD4olR80rDLd4uQol2XNmjLc1TY7j9ut5sfWtq6T8RhI2IlG0QQnsea6Yk0LxhLVpdVJt59w1g13tPc/zgXjLPpHH+XKYOVkvsyKMz3+Wfb6zkn2+spHpqbS6eMIeLJ8yh/dgXUVWVwux0PDlnydz1JZzeT8u+NxAVFUXzhrWk0BKYYPtMK1MSJZi1dK0lvrPQYquyuGpl+9eJK2RgEweXzDhK91lpdJ+VxuKdeazbttdI802jZF1CPR82by+NiA+2aOjRCMbFRDN3/EDq/Pwesd/O4fiHT7F7/X+1MlkSgahFRRRmubnw0wbyDm0nyVVI817Xmm2WJECC7TOtinf/8+6qjVzbTBH+OwsdRgwmruo9uyA1MYVJ1QvZviSLpc//JeJCh0YkR0aKq1or9ErIjI2J4t4h3Up/X/DpD/z4RQEdBt0Uts0SfRFlYkGJHaqqciHjFI6iQjK/XYbDoXDmWBJnNiwGIDUpxlC7RET0WX6i5KbqjXf/E0M+Czaf4/1d+WX2Ee07K6qqmm2DbzbOCMqw6e98Bse+Y2K/35eDmP7lWWjQTagLrjfuzGyGPfwKc4bEF9e90kFslpyjWNgWz0ocFqHCNlBueGgmx9PcFbbXr52qedj17TW72HLoHAqQXhDNZXf8A1dUdMjHE6VEgUR7zpw4wq4PX6FmUiz5+flMuKYN7RrLHEB/TH/nM1auXs+QK/uH3K+ILthER+j+p9cDfqeKC+3ZCgYjFb3IL4sRHidRyihYBXdmNlFRLlbN/Lshz8vtl7fn9t9+PnjiDI8umEK/sU8QFR2aZ0IKKnty+tivHFzxMv8eP5DoKNt0Bbqh1Sw/O5ZlMLJP1KL/MaMPt80bZmRStqgvi1GF2iLFVa0VZj4vTevV5Llh7Xlk7iPEVatNUVERLQfeTJ3GrQ21Q2IehQX5bFk+BzW/bH5gQv4ZZo+/nCiX0yTLrIUWA1m7lmUwso3Tov8xo022TRjRKIwI04WKDKWKh/fzMuY/2VSvXoM3powy7ZnxeIqYuHAdNQbcRf3m7U2xQWIcBfl5fLnwcZ6+qR3N6pu7ioOV0Sp05d1G26VtFrlP9IWu9lYSRhR6NqKIaDF9Xy/WbdvL4p15dJ1xisZPHaDrjFMRNQtTRLyfl1pRubiPH/L5zBgxgxTA6XTw0t0DOLfhdb7/4gN2fbOa/Ts26XpOibGcOXGEXd+sZtc3q/lywWSeG9ZeCq0w0WKWn13LMojcJ/rCLHul2AoCvV+WcDvcFS9OYOtbU7n9ut5l6l+JXPfKKJFhBt7Pizu7kPTsPKb0c/HftZsrfF9vt7beOBwOXhgzgLFN0rg9dR/tznzBpmWzdT+vRH+O79/FsY9e4vbUfdyeuo/Zo7vTuG6Nqj8YIbgzs7n+oVkMeWhmUG1OyUC2pJRQKOWE7FiWwWoC0kx7bZOzZQR6J4ZrEUe2Wk6AqPlvWuD9vExfd4ahraPoUs9F//r5Zb6vGfdMURS6tm4EQPe2F1HnuwO8//6rdP/DPWX3czpwuWQRS5EpyM8DFU4c2EX2t4t5ZdxAHA45jvbFoo824j5+iMxcNag2R4sBqx1zXa02WcpMe6XYCgI9XxYtZ7roPRtRq5kcVhOGwVLyvCz64STnsrJ564+xpF8oYnALB4+u//37ilCz7OpuzUiMO8rq/0wts/3I6SzqDbiDxh16GmqPJDC2fDCX6tn7iYtxUS8ljvFjBxi+ULlVcGdm8981m5nSz8U/N+Tz4RebDG1zRI4whIrVBGSw9mo5a1EmyJtE+ZuoReKkUfVHtKg1U3IcuyWL+qKyiQsjB/cSt2YMoKoq0xZvJK/NYJp26m22OZLfUFWVTctmMayVytXdmml+fJHL24TK9Hc+I/Pnr7ivKyzeUcCGYw769guvDZPYm6D7OpkgLx7e4TOt4shG5ASU2Pr0NdWZvng1vxxJq/pDlRzHKrH+cKgs30P0PA5FUXj8tt7UPPw52996nO1vPc7mpTMQdpBmQw7t/JZvFzxaev23v/U43702iVvboovQAmNzCI2gxKt1XVMPNeMdjOwUTXp2Hh9+scmWbY6R2DXvVusl6WQY0QTKh8/O5+ZrEkc2wqVbIg42/nqBRokeHp6xlA//dX/Ix7FKrD8cKgsfFFeWF98N/9Afu5f+/O2eo8x681n6jHxE5gbpzK/bN+La8z8W3tvbsPCgHcP7iz7aSP8G+TSp7iTKoZCaoDC0dRQbjsmlxsKlfN6tXbyiWqd3SLFlAuVv4qI13+FyqGF3uHrnBJQ2woPjGb/sOAuGJvCH9/bzy5E0WjaqHdSxrBbr1wsr5nFc2rYhLqeDp1/9G4k165b5W8OOl9G0c1/NzxkpSwapqsq2jxeRk36KwoJ82ifnMun2PobaIEIOodas27aXH34+z7+3FJXZXoQDz7bIanMCIVDB5EuY22HSkx4FwqXYMhhfN3HlviJhcnQqo6QR/mhPNkNauuhQ28WtHVwhebdEExl2GY0ZRfdW9Vn+UL0K21/+zxfsycmmba9rNT1fdnYWzcbOqLDd10LORqG1ACwqKuKrRc9xX+8aXNqmHYDhye5GrUJhNKK1N6ITqGAqL8xnL1vL2k3bLe8V1SPyIsWWwVg5fLZu214On7hQOrNu9+kCrm7h4v0Vv3Lm7HlLvlQl2GE0ZjS+hMC7n23mwLGPyecpnF5rMcbFxfO3lxaRVM0+NZ/CEYCnjhwkK/NMmW1HN33MXy+vR/dW9TWzMVis3D6ZhSgDNaNnifsS5lcs/IY/dYi3vFdUj8iLFFsGY+Xw2YoXJ5TOrOvd7veZdfe4z1r2pQJ75qiYhTsrj8semk/m0X3kX/g9ofTwJ/P4cfE0Wt/4N2rUbWiihebz0zefknJ4PZe3rFVme+uhTWhSz9xK71Zun8zC6IGaP1GllR2BhpHLC/OUWAeDGhWApwCwtldUD0+oFFsGY3V3th0bYzvmqJhNtYYtyvx+el0cc8cP5P65L9Bs6F9Jrd/YJMvMZc+G/9Es+3sm3GZsHlagWL19ChQr1wr0Jaq0siOYMHL5vuDc+VwoLKRN7VxAekXLI8WWJCjs1hjbNUdFC7QOj0RHuZg9/nKeXTqfX3ILy/ztaE4Ufcc8bptq9eknj/LDe8/RqGZ8me3dm6Zy6/XdTLJKTMwIwxntBdIKf6JKKzuCCSOX7wuKZ1a7OZ4H3Wf9Phi38kBcS2wttsJ5iUWJw0v0JdJzVCp7zvUIj0S5nEwe0avC9v3H3Dw27//of/c0orxyvUpITEzymQuVmJikiV1a4inIZ+/y53njwUHERNtDPOqJGWE4o71AWuFLVI0c3EszO8KJXNhtIK41thZb4bzEMmE6MhA9LKq36Pf3nBsdHmneIJXnhnfgiX9PIjYxucLfr+7ZlgtqFD1umehTjOlJ+VmHnoJ88rPSyc3NZffzwyrsHx/tZO79g4hyOY0005KYFYYz2gukBf7E3fk8beo0ghRMemJbsRXOSywTpiMHX41LicAxa4alt8DSU/RX9pyH2iGlJsWwa8FDPrdXRZO6NXj9gYF+/37oZDqPLJhM37HTiI6JrfJ4WuE96zDXfYTMLf+h/dW3sue1Rzjw9kTD7NCSqkS8UZ59s8JwZnuBQsGfuFu0ZhsupSgsO2QkR39sK7bCeYllwnRkY7ZXs+T8etes8fech9MhbZ4T/GoCgdK4bg1evLUTf537KCkXtdHtPOXJPXuG098sRy0qQs06Rfurb8PhtLbXqqpn3Ih3wMwwnBW9QP7E3UV1UsO2xew2LxKwpdgK5yWWCdORjdleTe/zD18cfs0afyPWyp5zUfPYeoyfxc4DJ/HgAL4s3e5QFNo1qsnnL47R5byffRBDi849AYiKTUCx+BJFVT3jRr0DZjxnoqcNVIZe4s7sNi9SsKXYCuclFrWjkRiD2V7NkvM3qxGlSc0afyPWyp5zUTskd1YezqRUmox+qcz2C6ePkvn5v6iRrE8H4XQ6iY4XLxE/VKp6xo16B8x4zmROUkXMbvMiBVuKrXBeYlE7GknVhJt3YLZX0/v8Z85mc1eXaB745Dz39fGEJPorG7FW9pzLDsm+VPWMl//7iE7xDJi7muv7dQ56/dOqkM+Z+Zjd5omOlrlsthRbJS9xKBdKNgBio2epArO9mt7n/yUjF0WBTnXgkhlHqZEUBwQn+isbscrnPHDCSfoXjaqe8fJ/VwovMKQ5Ia1/KhEfs9s80dEyl82WYqsEmfRnP0ru6ayla9m+72ip6NIi78Bsr2bF87sAFx2aB58AK0es2qFn0r/RVPWMe/+9qEjldMY5asQ5SM89aPn1TyUVKX+/S+5xQxnJ0TyXzbZiSyb9mY/W04m97+kf3tpI3XgqjMjDyTsw29uj5fnliNU/PcbPwp2VV2F7alKMrYSVL6p6xrz/XrIO6sR+KUz/0trrn4qK2SUXyt/vlavXM+TK3kLfZ6uWJRF+Wo07M5s//WMuZ86er3pnL8peqOJORmIs3p5FrY43pIWDmvFOYtQ8nhwUz8r1W9h7OI2V67cwsmvxizeyawIr128J+pmxE6s37+GVL8/QdcYpus9Ko/usNBbvzGPdtr1mmxYyqUkxeLLcHJgxqsy/U0smBxXSc2flkUkiabnOMv+2HzxNj/GzdPwG1qFkYCPfKX3Ruo0MlpL+taQNnXNjqvD32Yhr5s7M5r9rNtOnXi6FniJNnn/hPVuhhAJlCMV8tPYset/TRVvPclvHKGpF53FtszgemblUenHKcWWPtuSdTRN+lBoMWnqd8nMv0MjHrEb35/+qsG8kesKkZ1R/RIi+lPSvJW2o6DMSjSxL0r9BPikuD+7MbGqmJNKtejazl69l8l1DQjqm0J4t7wsbjKqsrKGQGIPWnsWS4wGs3HWO0Z1jSIlVuK65yu69v7LohwulHhw7eHHCIdT3RuIbd1Ye7e9+scI/XwLMLqzbtpfFO/PkO6UjZkdfStqJV4fWZOdP+xnSpnhVBpG9mEZds9Wb9/D61iyGLcvlklmnaPfiEd7bcYHla7aFfEyhPVuhxkzNTnSOdPTwLJbc05kbMxnaAtJyPABEuwq4p1cNaNBNiHtrdg4GyLo5kvAxO3/R7mjZRoba5pQ6JaLzubWDi5W7s5lYO0ZYL6aREasre7TlygY5TOyXwrTVGXywK4eVo+syfmVOyBNFhPVshZMzsOLFCWx9a2qFf7IBMQY9PIsl97RD80ZsOJXAyI9djPzYxYgVCDXiFiEHQ+baSCRio2UbGUqb491OZOXkcnULFzO/zqDzqyeF9WIaFbEq34YqRQUMalRA85pRYZ1PWM+WzBmwLnp6FkUWzKLkYMj3pnJSk2I45j7NhdNHy2x3ORWKTLJJEllo1UaG2uZ4txOpibVpCUxwnxUmQuALoyJW3tfGnV3I2n3nmXFtDO7M7LC8acKKLRkKtC4iCyI9ESF8Z/Z7I0IYtSo2z7m/OOm9XDJ8EdYsVGo0VrjHoqNVGxlJqTZG9Sve1yY96wJDW4CiQFZOLi1rJoc8eFVUVdXJ5DDZOENQw+yPbEyDx52ZzbCHX2HJsKTSEdGwJVksff4vul1DEe/T77V6+gvbaAdLJM5GrAw73mMrYkabE2nc8NBMjqe5K2yvX9tPoeleDyj+jiWsZ0srROyQREdW3g8eM8J3ot0nEcKoeiCKoPLVlhndvtn1HlsRI9ucSO1HtfSmCZsgrxVmJyxbDVk2IDSMniov4n0yeyq73fHVlhndvoV7j0MtUi2piJFtjuxHw8fWni05CgseLfOOImk0ZHSemgj5Yd4EMi07kp4HrfHVlqmqamj7Vv4ej+gUz4C5q7m+X2daNqod0DFE88ZaGaPaHNmPaoOtPVtypB0cWpcNkKMhfRCxvEMg07Ll8xA6vtoyo9u38vdYKbzAkObw8IylAX1eRG+slTDLKyj7UW2wrdgSsUMSHS3rmMiGVT9EXCGhqpCGfB5Cx1db9sEXm/jv2s2Gtm/e97jrjFNcMusUnx8sYuuugwGdV3ba4WHGYEX2o9ph2zCirDcUPFpOB64qzCVDSsHhfb1EnLZdVUhDtLCnlfDVltWKyqVjHaeh7Zv3PZ7+zmdw7Dsm9kth+pdnqzyvOzObD77YRHXHee7slijXqw0Ss0J5sh/VDtuKLRE7JNHRKgcgkPwdmbsRHN7Xy2p1zOTC8OHhqy075s7lu2Pw8UHj27dQ7ueijzZSKyqXs+cLeHNLJhMH1JSddhCYNViR/ah22FZsWa1DshNVjYZkwmVwWP16ydFxeIjWloVyP1dt2sMvxy8w49oYHvgkg0U7CnA5HUF12iKUvtCDqr6DmYOV8s+et62S4LBtzpaRyOnMZakqFz3bOAAAIABJREFUf0fmbgSH1a+X0WUxJPoSyv28umdbJvStxeCujZjQtxYjB/cJer1aEUpf6EFV30GkHE07XG+zsK1ny0hkSKwslTWgMqQUHHa4XqJ5ZiThEez91OIZFqH0hR4E4rUWJZRndQ+72Wji2VIU5RpFUX5WFGWfoij/8PH3GEVR3v/t75sURWmixXlFQM6yCg6RRmlWQF4vSTCI6GXX4hkWofSFHgTyHVa8OIGtb02t8M/c2n7WvN5mErbYUhTFCcwCrgXaASMURWlXbrcxQIaqqi2Al4Dnwj2vKMgHMDhkSCk4Sq5X1xmnaPzUAbrOOCWvl8QvIoZ5wn3nRSl9oTVWKqtgJVtFRYswYg9gn6qqBwAURXkPGArs9tpnKDD1t5+XATMVRVFUYVfBDgwjQjyiJYCGa48MKQVHyfX6ffHf3jJULfGJqGGecN95UUpfaI2VJo5YyVYjCKUf1EJsNQCOeP1+FOjpbx9VVQsVRTkL1AQqLqdtIYx4AEXLBxPNnkhA1E5UIhZ2rWUmWukLrRAlFysQrGSr3rgzs7nqwZdJUXKCese0EFuKj23lPVaB7IOiKOOAcQDzHh7OuKG9w7dOR/R+AEXrZEWzJ1IItRMVzSsq0Q87TKTwh1294aJ/L+/2Q3RbjWT2snWcyzjDqzfXZMr6wN8xLRLkjwKNvH5vCBz3t4+iKC4gBUgvfyBVVeerqtpdVdXuogst0D9xUbR8MNHsiQTCyZUQLX9HxORtuyAnUlgP0d8H0doPEXBnZvPuqo2M7RZNreg8rm2mBHx9tBBbW4CWiqI0VRQlGrgFWFFunxXAnb/9fBOwxur5WnojWkKiaPZECqF2oiLOkpWNt37IiSfWQ+T3QcT2QwRmL1tHjJrH2C6xpMQqXNdcDfj6hC22VFUtBCYAq4A9wBJVVXcpijJNUZQbftvt30BNRVH2AROBCuUhJGURbaQqmj2RQqidqGheyGAbb9FH/aIhSnkAb+Q99I/oYka09kMESrxat3WMIjXBQc14By5PbsDeLU2Kmqqq+jHwcbltU7x+zgVu1uJckYJoCYmi2RMphNJZipi/E2zemZyIYX3kPfSPyJMZRGw/RGDRRxuJIZ/3d6m8v6sAgHO5KrgKaHO66n5QVpAXFNESEkWzxyyskHQu2jTtYBtvORHD+sh76B/RxYxo7YcorNu2F1dsYpltyTFQv3ZqQP2jXBtRIgkCkfMsShAtfyfYELToIQyrhcfMsFf0e2gmoqdkiNZ++ELPZ9rfscMN1UvPlkQSIFYZrYvmhQwmBC36qB+sFx4z2l4r3EMzET0lQ7T2wxd6PtN6HVtYsRVuuMYK4R6JtRA5z0Jkgmm8RQ9hWEVwl2CGvaLfQ7OxgpgRGT2faT2PLWwYMdxwjRXCPRLrIEtfGIPoIQxRw2P+Qh9m2Cv6PZRYGz2faT2PLaxnK1h16e3JUlXVUqNPifjI0boxiDzqFzk85iv0YZa9It9DibXR85nW+30R1rMVrLr0bmxEHX1KrIscrUtETWz2V7NJVHslklDR85nW+31RRC3k7p7WUk1NdOHOLmTYkiyWPv8Xv+rSnZnNsIdfYc6QeMb99zxFqsqHt6YQ6OclEpB5fpLKueGhmRxPc1fYHujUb72Y/s5ncOw7JvZLYfqXZ6FBNybedpWw9kokoaLnM63JsXs94GsdaEBgscX0tqWGeTcgPnf1amymfHySnac8fDi6AYF+XiKB4udo5er1DLmyv3xWJJagZKC5ZFiSHFzqhMiDMJFti0gqEVvChhEDDdeUT1we3AK2H79A51dPynCPJGBEXz5DIvGFDBXqj8iTrUS2TVIWYRPkt741NaD9yjc2PVvVZUJf6cmSBEbJyLBzq4a2KusgR7yRgeg1m6yOyKU+RLZNUhFhxVagyMZGEg6LPtrIqWOHWP7rET4fWwcIbBZKsGLGaPFjtcKbktCIlNwrswYPItfWE9k2SUWEDSMGioir3UusQcnIsG/jaAY1KqBaXPHrEEgoJlj3vZHufhkSldgNM8JlItfWE9k2K2LEklaWF1tWwmprqtmdkpHhrpN5/O/nQtq9eDSoPMFAxYzR4keWPpHYCbMGD1Xlw5nZnstcPW0xQsxLsWUgMpkxOPRebLRkZLhi7EVsfLAJDVOTWDXz71V6R4MVM0aKHznildgNswYPVdXWM7M9l3X/tMMoMS/FlkHI0E7w6NmYhToyDFbMGC1+5IjX/kSSh9zMwUNlKSpmt+cyfaYiob4XgYr5cN87yyfIWwWZzBgces+0CXViRbDL9hi9zE8kTRj5ft9J3l7/Mw6HPmPG5nWSuPe6zrocOxwiafKDqMtkyfY8ePSe5BDKexHMEj3hvndSbBmAyGuqiYrejVmoI8BgxYzR4idSRrab9hxl5ldu+tz5rG5i68D3G3hi8SdMGdELRfFbq9BQIm26v4iDB9meFxOseNJzkBDqexGomNfivRO3gvzGGYIaFjzeFe5Lt8mq9n6RVbEle4+k8dORMz7/lp6Vy5pjLvrc8YjuIujXHd+St20p/drVq3Lf/hc3ISUxTld7/C3NIxJ2r/Em2/Nigllxw3tJvfErczRvy0N9LwJdoifg41dSQV56tsIg0EZFxNGZyIgaOjASu3dYlfH1riPM+SaDxj0H+/z7G/P+j/xCD5+u+arM9sTEJB6d+a6mtjS5+FLO1LmITekVG2RvPJ5C3p2/iFlje1EjWZ/7ZRWPit3DnLI9D97To2ekIpz3IpBIgFbvnRRbAeCv4wu0UYmU0I5WyMbM3h1WYaGHIj8e9a93HeXNHbn0u/Mffr1WBZ4imt89s8L2Awsf0NTOEmrWqU/NOvWr3K9ek5ZMeO1xpt9xCTWS48v8LToq/KbWCoOQSAhzyvY8OPGk9yBB7/dCq+NLsRUAvjq+SGhUzCLSGzM7P1vrdhxixhe/klyzrs+/J6Q2oNeIYcLkSAVDfGISl901jUf/9xp4Cku3ezwe6iuneebOfmF9LysMQmTiuP0JVjzpLYb0fi+0Or4UW1Xgr+OTjYpEL+z6bK3edoB39xRx9YTnLCmmAiE2PpFewx+ssP3ITz/w93+/w7/u6hdyQr/ogxCrhDkl4RGseNJbDOn9Xmh1fCm2qsBXxzdycC/ZqEh0wQ4dljszm8cWbyYqLqnM9qKUBlw2/G6TrDKXRm06c9zpZMzcxcTHxZRu9xQWcm37mgzt1cpE67TBCmFOSfgEK55EHyQYhRRbleCv4zufmy8bFYkumN1hhZuYfyr9HH9+Ywu9x04jNj5RBwutS/2WHanf8pkK2z/93+vkb9jDzX3bmmCVdlghzCkJHymeQkOKrUrw1/EtWvMdLocqGxWJ5pjdYYWSmL9620HW7DgCwMFMD33ufoqYuPgqPhU6iYlJPpPhExOTfOwtPl2vH83aj99iw9zPSYiNpmZiNH/9Yw+cTmst8CE7YYnEP7ass6XVtPlAa3BYGTuXGLDzd9ODUGrhLN2whzXumnQefCcAiqLYNh9Lb4qKigBIO7yPY6tmM+Oey4lyOU22SiKRBEyk1dnSatq8XQRVZdi5xICdv5seVJaY787MZu+Rst62H349w49qc7pef4cZ5tqOksT5uk1a4Rz8Z+6b8wqjBzQvs0+1xDjaNa26wKpEIhELa/mpA8DsBUKtxM+HTjFv2WpmDK1pu2sV7HMQSYv7+qKyBX8PnjjDhDe3sSz74jL/jje9kS7XSaGlB7UaNqXVsMcqXPMXtqgs+PQHs82TSCRB4pw6darZNvjmyOapoXxs7vJ1tIo6yfXtEjiTlc/2k4VcdnHzqj8Ygdz99Jv0rJ7JFS1iyPMotrpWc5evo7nzOO1SLlCoOtlxylP63dyZ2dwx9TWuuKQt8bHRpfvv2LGDCx6Hba5BMJS8N4NaFudaxUc7OJOVz+c/n2X5rhz63z2NOo2aU6tBk9J/1VLrmGy1vYmNTyhzvWs1aEKjtt3YfTidg7t3cEkr6eGSSISiUc8n/P3JVp6tykbnkrL8fOgUO3/az197xXI26zy3do63zbUqeQ6uaw6egnyua66W+W7e4UXv/SPZG7pu214W78yj+6w0mjx7lFrTjvDs+ize3bCPfndPwxUVbbaJkt9oN+APHKxxKaNe28Go13YwZsZqLuTl63a+SPf6SiRaYKsEeblAaOD88eFZdHQdYtrlCZzM9kBUPIt3qba4VtPf+QzPkS3c0CSXxtUcHMosYsWvcTgbdWfk4F4VksDfXPm18Iv7BoIWEwLmrPyevbEdaDfgDxpbJ6mKZyaMIDs7q8L2qtZ8zDh9kh/ff5q59w4s9dRqSTALDkskEU2kJMibPW3eKrgzs9m66yCH4lQ+3neOoiI4nZNFrerJNLTBtVq3bS8/HcxiwcZ8kmMVzuWq4Cqgzem9AGWSwGcvW8vaTdsNKSKq9+zIUCYEXMjLZ/I731KgxFBQUEhMy1606ztEc9t8Eaq4sCvZ2Vk0Gzujwvaq1nysXqsuF4+YzD0LX6BGQgx5+Xnc1b85Pdo0CNsmI5eOkrOHJXbGVmIrEmYPasGijzby1/41besBfG3yKIY9/ApLhiWRmujCnV3IsCVZvPDnYdz71IIywuqKhd/wpw7xhhQR1XN2ZCid4vkLeYyft44Owx+jei3faxXqSajiQlKRlJq16HfvcwCoqsrMt57jHk8Rvds3Cuu4Ri4dJWcPS+yMrXK2JIHhnZ9T8m/xzjzWbdtbZj+r5mr4K0b7yMylFbZf2djD61vPVXktwkXvvLCynaKjNB+tPD/sP8kLyzfzwvLN3D17HRePmGyK0JLoh6Io9LnjEeZvyebJxV/xwvLNLF7zI8GmjGidA1tZeyLzJiV2x1aeLUlgBOoBtOpI01842X3uCEdOxJbbHkuH5voXqdXTQxDoeoobdx9h7reZdL7hz8Udclw8UdEx/g4rsTCKotD7tofIyTqLqqps37eTn975hCdu6x1w0Vmtl46qrD2x6+Lr4SJDq/ZBii2JT4zM1dAa0cLJei8u7a9TfON/X3FD/y54ilT2Hstg+V6VPnc8Iiu8RwiKopCQXA2AFt36cSg2jkffXMqogW0AaFirGonx/sW2ljmwlbUndlh8XS9mL1vHpu17mb1sLZPHGJNLKdEHKbYkPpEjTe1GlXovLu2rU1RVlextW/gpoRuxCclEx19E79sGSaElMHqv+di4/SWcTEhh1s+7ADi9/EteHd2T2tV9H1/LQUtl7YnZi6+Lijszm3dXbaR5dVj86Ubuu2lgxItPKyPFlqQCPx86xfTFq1lzT30gckeaWoVR9Z4lW75TVFWVSYs2oHT6E0069Aj7+JURzoxCuy0oHS5GzMCs26QVdZu0AiD30qt4YOFkXh7ZnXqpKVV8MnSq8lzJWeS+mb1sHTFqHvNvSGT4svPCeLdkaDM0pNiSVOAfs5bRKNHDyt3ZTKwdE5EjTS3DqHqGNT/Zso+3N50kLj6xdFtRkYeGlw6nUZuuAR8nVNEUzozCSCzvIBKx8Qn0HfdPHl06A5d6kLzcCwztWJ2b+rbR9DxVea5EC/uLQIlX666OUbROdXJbxyheE8S7JWIurxUEoBRbAWKFm1meUGx2Z2aze++vTL8qhgc+yWDRjgJczuJJq5E00rRCGPV/3/7CisNxDLj3mbCPJcswRCYxsXH0vuPh0t/XfPQmhet3c0v/dpqdw2jPlRXb6vKUeLVGdy4eRI3uHMM7O7NN926JmssrogAsjxRbAWKFm1meUGxe9NFG7ulVg8FdU/g52z61t4JB1ITdoqIinl66ifQcFU9REXk1WtLjxrtMs0dSllC9gyIVd+0y+E6+WvUOXy/YQJTLSVI0TB7eE5fLGfIxjfZcWbGtLs8Ha79jYBMHaTke0nI8AAz8//buO76q+v7j+Ot7780kCQESEnbYsmQIyAxua8FZxS1BhoJgqdZKxYECldZKreLAgiIFq4J1FFonw4EiolZFyyxlREYgAcIIyb3f3x8ZvyQkuTf3nnvGvZ/n48GD5OaOz83JPed9vutkuXh95QZLw5YdT0LNCoChhngJWwGwa5qvSzA1Vw8ZwzvHc/7z73Npdi86tmpqRtm2EK4Bu6F8WL1eH1PmryL93HF0adcl6BpE+ATbOmi3VsWeF99Y8fW+Xdu4Y95c5t52LjEhBC6zOHFfXZPWmU34eJ/m439WvtVD68wmVpVk25NQswJgqCFewlYA7Jjm/Qmm5uohY8WPhbRK8vKbp5byxh/uMKNsWwhXt0d9P6y79ufz4b93AvDpf/bT+pKJFYObhTBDRqv2uC+dwvin5zCsawYA2d1a0q65dQf9ujhxX10TO45js+OsUbMCoBEhXsKWH3ZN83UJtubKIaPE6+PI0UKeuiSOu97bwcHDx6o8NhLGRdQmHDu6+n5Yt+3J475lP9DjsttBQbe+jWmQHL4ZY8GSGYWRL615GxJHzWR3QR5ouP/NF7nvkmK6t7XXlQecuK+uzOh9qtHPZ8dZo4tWrOWSdlBQkE9qQpOwBUAjQryELT/smOb9CbbmyiFjzpL3YM+GirFb1R8bCeMizBTIh/Xg4WOUeL3szjvCY+/+j3Num4nHE2NKfcGGJplRGB0Sk5JJLPtbSB/zEL97YQaThhbRvnkj3C4XaalJfp4h/Jy4r67M6H2q0c9nx9a21V9t5j//PcqTa06SkHCClAbxgLEB0KgQL2HLDzumeX9CrdnfH1ekjIswSyAf1uf++TWf7oujQWoarpgUzhn3CG6PeR9PCU0iUC63m2FjHmTJh6/j3VLIiaMF9Ewu4K4rw7ummz817fd8Pk3+2lW230cZvU+Nln30Cw/kMPI3f+bZERlMWH6cpY9NMfx9GhXiJWz5Ycc070+oNfv744qUcRFm8ff7fPofX7EtqRfZN19qcaUiFMG2DjqxK9blctHrwmsqvt+y7n1mL/2IqdcMsKymmvZ7c5a8x/L319S5j7LDkAij96nRso82430a1eCi6nsleNOsfSqgwuzwQYk0l909l9z9eafd3rxpWsWZxGsjk0lL8pBXWMLI146G5YwiUlT/ffp8mj35RSQmp3DRRReR3HkAnQdcbGGF5rLTUgfCONu+WsPBb1fidrvxnTjMH0cNJKVBgmX15BUUlrV6JNbZ6lEeyEZcOMySQFJep1H7VKOfz65s+T4HTa71emiOb9mSsUPGq6tlbM6S90wbFxHuIG1WUK/8+yw8XsTE59dw/fXTSG0SPctpVGa3pQ6cwMiAGq6w277PMNr3GQZA4eF8Jjz/ME+PHUxqcmLQzxmKulo9yj/7j068yvLuNqPHmjl97FqgnPY+HR22oqVf2k7MHMNWHqSfXrqKf2/dbXgoCiaohxLQjhw7wcR5H9P75gdIaZQWTMm2IC1T5jMyoJoRdpMaNqJfzsNMWDCDlg09aK25tF8Ww3q0Nuw16uJvnGT5Z//euUst724zep/qxHHGwXDa+3R02IqWfmk7MWsMW+UgfcVf15KZiKHbN9igHmxLasHR40ya/ylnjZpOUsNGoZQedv7ClLRMiUA0SG7IeZP+CJReHH3R0rmcPLWdi89qF/bXrqvV45bhg1i+Zj2/+1kjbnp5G89OagNYt1SE0ftUJ44zDobT3qdjw5bT11QRdSvfWTZJdBOni5hxfiMeXGPc9g0mqNc3oP2wYy/bcvPRwCvrdtM/52FT18qqHpoOH8zDp30o7SM1/f/XSKreIiVhShhNKcWAkZNZ9vozFJdsYcTZHcP6enW1egCM6OBi7Y4T3NDdA8UngBjbd0MJZ3Ns2LLjJVWEMSoH6UVfHubGHjGkxxZxSbsEQ3aEwQb1+gS0dzds5+Xvi2nR50IABo7pQHyiuX9P1UPTnh1biEtrTe7CKVVulxAlzNL/FxP5x5vzKfZu5spBwV8Nwd9+urZWj8qDqm99JZfdBV5e/GYf6Y1O4HKVjm22azeUcDbHhi27XFJFGK881AAs33iE165OpERrft5eM/n90Fq38goKuejOJ7i+a/2Cur+AprWmuKT0grHvbvgvb+2IZciNzgsxj066nvy8/Xw7d0KV293xiRg1r8wOSx1EwkWjnarvFWN5b/lCij/6gSsGlgauGI8bpWqdyHWaYPfTlU/S3x5bOn5szkeHocVZsr8XYeXYsGWHS6qI8CgP0nPXFnB5Byqueh/rKWZEh7iQgvCiFWs5kHeQv3wRx6sbT1X5WV1Bva6W1CnXX8CvX1hDnicTt8tFw+btOPvqK4Kqz2qFhUfJvG4mcWlVBzLnLpwC8cbsLuwQSpx20WgjA6odwm6fETl8/skK/vW3Tfh8mgbHd/Pk+HPxBHCx61D2004bVC0ih2PDVjjIgHt7KA/Sl909l4/35VW78n1R0DvG8p30B7e3rvdqw7XtpJvt3cT/Cj00PudWurTvVu+anMgOB+toY2RAtUPYBegyZDgwHIB9O7cyad5cnrrtPGL8BK5Q9tNOG1QtIkdIYUsp1Rh4FcgCdgAjtdb51e7TC3gWSAG8wCyt9auhvG44yIB7+zF6x2jUTnrn3kPM+Pu3xCY04NiJItLOzyEzq7OhtfoTzu4st9tNUd7OKrcVFx4iKa09YJ+DtYgcGa074Br+S8bOe56kxDhOHj/GvZd3p1PLqkukyH5aOFWoLVtTgQ+11rOVUlPLvr+32n2OA7dorbcopZoDG5RS72qtC0J8bUM5bYE0UT9G7aS35x7kvmU/kD12JjGxceEq169AurOqt0BVno1Y/X6VZbY6fWp+UVpTx4esygE1P28/e3ZsAUrDZU3vWYSPv5MFb0kJ0xdM5/4RXrq2yaj4ueynhVOFGrYuB84p+/olYDXVwpbWenOlr3OVUvuBdMBWYUv68iNbKDvpN9ZuZv2WvWgNOwrdDBv3CJ6YWDPKDonTw5HRKgfUb+dOqBiXVr0VT4Sfv5MFt8fDsLEPM/OFR2iTsAmloGfbdNlPC8cKNWxlaK1/AtBa/6SUqvP6I0qp/kAssK2Wn48HxgPM+821jL98cIjlBU768iNbsDvpv7zzDd+rznS97k4A2rpc9Zo15TTRMh7LHZ9YOuif0i7SorTSXVckXjTaqVxuN+eMnY72+QBY99k7nJ99jF9e3tfawoQIgt+wpZT6AMis4UfT6vNCSqlmwF+BUVprX0330Vo/DzwPBHwh6kDJ+lnRLdAwXXSqmK827wbgkx/3ktu4H92HXR7O0mwlWlrDuo19vOLr7fMnM2vhcr+PkWUfzKeUQrlLB8x3GTKczetieGzZJ9xz9dkWVyZE/fgNW1rrC2r7mVJqn1KqWVmrVjNgfy33SwFWAPdrrT8PutoQyPpZwp8TRaeY8OxqGva5FHdMDMk9zqNrh65Wl1VF+QG/8pgjkHFHwdq7azv5efuZljOiyu01BShZWd96nc6+iK3rPfzu1VXcd+0Aq8sRImChdiO+DYwCZpf9/1b1OyilYoE3gEVa66Uhvl5QZP0s4c+xE0VMmLeaHtdNIzUtw/8DLFJ+wN84/24OLp9TcXtx4SGOpzWV7qwAbJx/N96TxwEoKSlGa01B4QlcMfGkD/8lAHtefdDKEkUtyk82ik8U8tjid0hNSUYpRVpyHF88e4fV5QlRq1DD1mzgNaXUGGAncA2AUqovcLvWeiwwEsgGmiilcsoel6O1/ibE1w6YrJ8larLux9388V9baJDaBJ+Gnjc8SErjNP8PrMaK7qXK3WAQeFdYNCsfb3Uybz+Z180EwFtSjHLHEtOkJT+9NKVi0Lyv5pEOwiDBjn2r3Lp4bOf3HN2yHq3gh/XLyT9ynEYpiWGpV4hQhRS2tNYHgfNruP1LYGzZ14uBxaG8TihkXRZRk0837mLeugIunPxYyAPepXvJGcqD77ScEbTIKr0Q8s6tPxLTpKWVZUUlI05CGrTuToPW3QEo3LqeiQvW8tToAaSlJoX83EIYLeJXkJd1WQSA1po5b25gZ0EJAMfi0hly870RPbMwUslAdVGdy+Vm0JgZ/GrxbBonKLxeL8N7ZnBJvw5WlyYEEAVhS9ZlEVprHlz8Cb5uV9D9UhlU63SRcH1CYbz4xCSyx8+s+P6NN+Zxqngzlw/qZGFVQpSK+LAl62dFp7yCQhat3IhGsXlPPunZN5PVrZ/VZYVMDvhG0xTn7QLAW5hfsfaWqmHMViitZk5qjXNSrXXpd+Vt/PPtBax/aQ2NkhNISYhhzMU9cblcVpcmolDEhy0RffYdOsIvF66nz3X34ImNo3tsHPGJkTE+z0kHOzupHCAOH8xjw+xrAfAVn8JVdjUAFz6S4kt3iUlpHQ19fSeN67NzrfU92eh72RiOHT2Mz+tl596d/PL5RTwx7lzcbucHLlk70lkkbImIknvgMHct3sCQcTOJSzBnZpK0NoUu3K0pdQUImcXpHMH8LTRIbghAcmpjYhMaMGneMzw1/lw8HrfR5ZkqlLUjJaiZT8KWiBi79+dz98v/Zui4mcTFJ5j2utLaFDo7t6aIyJHZpiOun09m4nNP8vTt5xHj0MAV6tqRssi3+SRsiYiwY+8hpr76PcPGzSQmLs7Q546UMSyRQloSRX1V/wx7i0/xyoqP6NS6KV/Oc16gD2XtSFnk2xoStoRjLfrwez7ceoyYmFh8nkSGjZ+Bp2z8jZGk1cVeJOA6l1UnLjV9hk8V7GPT85MZ+8LXHD+Sz32Xd6V725ouA2wvoa4d6eRFvp3c/SlhSzjSgvf+zTe+jgwZc43VpQjhl5Na48JZazhOXIINcLGpGSQ0zuDsW+7H5/Xyuxdn8psLNL06NAu6FjOEsnak0xf5dnL3p4Qt4QhFp4p5+JXPOel1cfJUCbHtB3HmeVdYXZaohd26Xq0OO05qjXNSrWBMgHO53Qy79QGeWPIYjT/eDsAZmUmMv6SnYXUaJZS1I528yLfR3Z9mt5JJ2BK2d6LoFBOfW80Zv7iHtplyaRUnqO8BMNxhqDxAVA9oKuGuAAAfEUlEQVSBhYVHmZYzQsbfCVwuF4Nvvrfi+y1ffMDspWuYeo29FkIOZe1IJy/ybXT3p9mtZBK2hC39Z+cBPt+UC8DK7/fR/brf0ijd/uMpRHDMCjoy/k4EqmP/C9j2VQwz/vYe91830HaX9gqmZcapi3wb3f1pxSQBCVvCdtZv2sOf1+zjjItuAqDf2enEJ1p3cVmru6CECIRZXbd26yL259FJ11dZyLac0j5atq178dr2fYaxwx3D9CX/YPqNg20VuKwev2RmN5zR3Z9WTBKQsCVs4UD+UXxas3FnHi9+WUj26Ptts2Oz4wFEiOrMarUL5XWsOHEpLDxK73tP/wxvnz85oM92Vs9B7HR7uO+l15lyWS8AUpMSiIuNMbzWQNlh+QYzw56R3Z9WTRKQsCUspbVm5iufsc2XSXxiEjENWjB01JW2CVpCCOOE48TFjADXunt/cuMTeWjNegAK/ruOJ0cPoGkja1q3rV6+oT5hz4gWMCO7P62aJCBhS1hGa830JZ9S3GUEg3sOtrocYSDpehVmMavluXmH7jTv0B2Ak8ePcef8B3hiVD8ym6SY8vrl7LB8Q33CntXdndVZNUlAwpYw1cHDx7j3r5/jSUylxOsls98VtO1+ttVlCYPZtetVQqAwQnxiA4aMn8W9r84hQXkpLi5mePdGXDW4c9hf2+rlG+oT9uzQ3VmdVZMEJGwJ0xzIP8rkF9cxaMwjJDSQg5swn11DoHCeuPgEhoyaVvH9+8sXUvLRD4zM7hrW17V6+Yb6hD2ruzvtRMKWMMXeg0eYsuhLBo+dSXyi/VcqFs7htNlx4WJWq53TWgfNqrfPiBw+emcJRSu/5+bzuhv63JVZvXxDoGHPDt2ddqK01lbXULO1T9m0MFFfew4UcPfirxkybgZx8QlWlyMizLScEbXOjpu1cLkFFYlo9u17r9DHs53RF9lv9XkzzVnyHuzZwF3ZDf//to8OQ4uzIrd1a9DkWmd2ScuWCIsNm3eTm3eUEq+PV7/KY+j4mcTGxVtdlqiDtBAJEbozL7qOb1a+zqOvfEr31o1RSnFR3w7ExtTvcOvkiy6D9d2ddiNhSxhu8cqNrD7YiKZnXAjAsPFd8MTEWlyV8EdWVxfCGN3P+wX7dvXhs8IjFJ88zhvPvcrT488hPi7wtbnsNouvvqzu7rQbCVsiZFprSrw+ABav2sjXJe04+8pr/TxKCHNIi52wQkarthVf57fIYsJzs3lybDbxcTG4lMLtdtX6WDvO4hOhkbAlQnKquIQ7nlvFqeSWKKVo2rEvPfpfaHVZQlSQFjthtUZNm9H12vuY/PrLoH0cyctl2qVncFan5jXeX2bxRR7bhy2n91tHspNFxUx8biWdrrqHJs1aWV1OWEnriH05bXaciE6paRkMvuFXAPh8Pv700qNM8voY0KVllfvJLL7IZPuw5fR+60jz7fa9/PmdTSQkJHLk+Cm6XTOVxk1rPjuLJNI6Yl9WhV0J4CJYLpeL7Jz7eGbxY5R4fQzp3rriZ1YvWirCw9ZhS/qt7eXLzbn8adVPZI+djctV+3gDETorDuR2ayGye5iRAC5CoZRiyE33MP9vcyjx7uCcnlmAzOKLVLYOW9Jvbb2XPviOTXvy8fp85HobkT36fglaJrDiQG6HAFOZhBkR6ZRSDLr+Lha99hTL168kNsbDJecN4vaf90apWpdsEg5k27Al/dbW+92rn3O4zXm0uy4bgA5ut8UVCVF/dmuxs5rdWwwDEQnvoZxSioHX3onP6wVg13++4rcvLeXRUdkSuCKIbcOW9FsbL9DJBlprHvnbWk52+jkdeg0xsUIhjOe0g2+4RUKLYSS8h+pcZSezbbr1Y7fHw93zlzByYBYAnVtn0Cgl0cLqRKhsG7Zq67dO3/Mjn363XWYnBiGQyQZaax5Y/Cm62+W0O3OAyRXal1GtI5F0Ri6ECFx9PvstO/cmLyWNV3duBeCnBcuZc9NZNE9veNrjhTPYNmzVtvrsnCXvsfz9NYa2cEXD8hKBTDbQWvPblz7C0/sasrr1s6hSezIqCEXiGXm0snv3ZG0H94IDey2oxngb59+N9+TxKrcVFx7i0UnX2/LEpb6f/bRmrUgrW1KnQ6+B/OovD/DH63vSKqNRWOsU4WHbsFWTcM1OjIblJWqbbLDv0BGmLFxHXGoG2qdpO+gGWnTqZXW5Uc/uB3Iz2P13EM4DuhEtoLUd3DfMttfVHYJ9r96Tx2me80SV24rydlL4wZOG12i12Lh4ho2byT3zH+TRkd1o26yJ1SWJenJU2ArH7MRoWF6itskGFw3swcy3fmTIuN8Rl3D6eADp8rKO/H6j+3cQTS2g0fReQxETF8ew8TP47V8eZMZVZ9CxZbrVJYl6cETYyisoZPSMlyjIP8QbN5T2WRs1OzEalpeoPNngze+P8cXuU7hKTpDzp38xevYSYuPia3yc7ASNd/hgHnt2bKnx9nCS4CzKuZTL1i2GgUhKSiY/bxtFeTur3O6O8BnTnphYho2fwczFvyfVvQ2t4aw2SYw6v7vVpQk/HBG2Fq1YS17u/8hMiSEtqbT51IjZidGyvET5ZIO5n+3mhM9Nw+QkIJmk1IRag5YID5/2EZfWusptJaeKKPEWMy1nRJXbjQxC0RycJWhW1bBJGrMWLre6jJD8du7fmJYzghZZHU/72XYL6jGTxxPDkJz7K77/ZvWbHF/xNROG97awKuGP7cNWeSCafk4cE5Yfo9eTe/FUulp6KKvqRvryEsUlXha88w3DBvfnQMExjmX25cyLrrO6rKimtI/chVOq3FZSUoyC08JQNAQhM0Rz0Kxu4/y7OZm3P6zBXtQsXGMQu55zBT9+EsNTb3/J5Mv6hvRcolQ4Js3ZPmyVB6KLezZj0uHD0OIsw4JQsJdFcMLsxVPFJdzx3CqaXziehmmZNHN7SExOsbqsqJeannnagX/Pji0cXD7HoopEpKrp4H4ybz8tbnyUzFbtqtzuxOBp9wkU1YUzzHYZMpxNn3t4/O9rufuq/mF7nWgRjklztg5b4e7mq215CX/sOnvx0JFjHMgvRAN/fOvftL/ybtKatfb7OCHqIt1w5jMiSNS0babljDgtaFkt2Pcqf3tVdR5wMVvXe5j1ykquHtgegDaZjYmPiwnpee3UuGBGLeGaNGfrsGXHbj67zl78bvs+Zq3YSnrn0mbkztdMJTW9WUjPWXknePhgHj7tA0q7wsq7IeSAG/mkG8580fSZiqb3Gm4d+p3PnoZNmbtpC1prCl5fxTO3DSWlQULQz/nMstWs+/dmnlm2igfGjPD/gDAyo6EjXJPmbB227Hj1czvOXvx6Sy6PfZjLueNnVFzywQiVd4LTckbIAdcANZ3F5+ftJz6tpemvW367ECJytOjUgxadegBQ2Pc8bp83nafHDgnqcj95BYX87d21tG8EL7+zlolXn2tZ44IZDR3h7E2zddgKtpsvXOw4e/GL/+zhyY/2MezWB3C5XP4fICxV01l8eTdd9TBkZBByeutBKF2ZEjRFtEpq2IizR89gymtziXH5OHGskNFDWnJB77YBPf6ZZauJ00U8f1kS1y47ZmnrlhkNHeHsTbN12LIbu3Vrrv1hF89+VkD26PsNvzp89YNbft5+9uzYgtvttt2YD6dzehAyQyhdmfL7/X8SPKNPYnIKQ3LuA0ovyfa3ZU9T4t3Gz/q2r/Nx5a1at/aIoXOamxt7xPCCRa1bZjV0hLM3TcJWPVjdram1Zu7yr/lv3gm0hsMx6Qy95V7DgxacfnD7du4E4tJan7aIoBDCPvy1AErwjG5KKQZcM4nX/z6PEu8WRpx9+jpl5cpbtUb3SgJgdK84lnxXaEnrllkNHeHsTZOwVQ9WdmtqrZm+5FNKulxKl0sGWVaHME59u8asmhVYn9YQmbloLZnMIALR/6rbWP72Ak59uomrBneu8T5/X7WBc7Nc5B4pZv8xFyg4N8vF6ys3mB62rG7oMIKELRs7dOQYy9dtRQMbth0gecD1ZHW3Zg0Vd3wiuQunUFx4iKK0phW3S/dD8Op7YLTqQFqfkCQHeyHqz+yTlPLXe/lIPmP1KdxuN0op2mSksv650kaF1plNWLH9BMs2HichIZ6UBvGAh9aZ5l8E227jt4MhYcum9ucf5c4X19Hlsom43R7a9EompVGaZfV0G/s4UHrQdPqlPoQQwk7MPkmp/HpF+fvweYspKTzEptcepqTEi8fj5oUHchj5mz/z7IgMJiw/ztLHpthimSOnkrBlI4cLT1BUXELB0RM8+Pr3DB47k/hE+eMWpay6iLUdyMBuIcIjrlFG6RdpLfEkN2HSvJU8ddt5tlzmyMkkbNXAihVzX//kPyzbeIKU9GYol5sh42YSFx/8QnShkoOb/dR0Eevy2yOdjPcSov5q656s7QTNExNH6xFTuPWJ37PrP9+w7LrSS7zZYZkjp5OwVQOzL8fz6kc/siY/nfPGjAr7awVKDm5COI+cJInKauue3DD72lofk94ii88T21BctJakuFTA+mWOIoGErWrMvhzP4pUb+ex4C3oPvzFsrxFNnDQbrr4HRqV95C6cUuPtdiEHe2vZ7W9cOFPu1u/JL06i1aN7cCnw+TRNU2Jo76DZf3YjYasaM/upX3z/W74qaU+vn40My/NHIyfNhqvvgTE1PdP27y2SDvZOCu7C2cw+SVHaV+fr3faHxVVu9/l8fPTiLH51bmZY6okGErYqCfcqtUWnipm97AsKi3wcO1lETIdszrzwypCfVwhhPCcFd+FsZof31PTMes0qd7lcZI+expOL/0DTT7ailKJTsxTG/axnGKuMLFETtgIZ9B7OVWpPFhUzcd5qOl/1a5pnhveiwyIySRedCJSVrXLR0CIYDe+xOpfLxdBbplZ8v/XLVcx65UOmXTfQwqqcI2rCViCD3o1epXbHTwf5fscBAJat20nXkVNp1LRZ/YsXgsjqohPhZVarXE2hIz9vP/FpLSvW5gvXa1vJKa2e4TxB69D3XLZ7Ypi+ZAUP3TA4LJeNiyRREbYCHfRu5Cq1X27OZc7KXNoMuhyAXrdk0SAlNaTnjMazKSGEfdUUOvbs2MLB5XMsqkhUFu7jQrteQ/if28MDi99ixk0SuOoSUthSSjUGXgWygB3ASK11fi33TQF+BN7QWpu69r5Zg96LS7wArN+cyzOfHmLYrQ/gcrkMe36nnE1ZSbrahBDCPG16DGCn28NvX3qNR24sDVxulzL02BcJQm3Zmgp8qLWerZSaWvb9vbXcdwawJsTXq7dwD3ovN+uVz/jhaCIxsXEkNGpKds5tkvItIC18wigS3IUITOuufcmNiWP8y+8BcOLATp68dQAZjVMsrsw+Qg1blwPnlH39ErCaGsKWUuosIAN4B+gb4mvWSzgHvQNorXnk5bUUnTGcc3oODvn5hBD24MTgXj7UID9vP9/OnVBxuzs+8bQxVEIYqXnHHjTv2AOAohPHmbLgQR6/sQ/N0xtaXJk9hBq2MrTWPwForX9SSjWtfgellAt4HLgZOL+uJ1NKjQfGA8z7zbWMvzz08FJ50LvPpzl4+BhNGjagZQiLsx06coz7lnyBJ74BRaeKyeh/GW17DAi5ViFEYGT8Ys3Khxrs3bUdr9dbcfveV+5n+/zJprTKud1uigsPndYqGEktgtLqWbe4hESGjJvJr/7yAH+8vietMhpZXZLl/IYtpdQHQE0rmU0L8DUmAv/UWu/y162mtX4eeB6AtU/pAJ+/TpUHvc9Z8h7L31/DiAsHBx20DuQf5c4X1zHg1kdIlA+WEJaQ8Yt1y2zVrsr3RWlN67WuUqBqCx2tstpHdOiN5PdmlNi4eIaNm8mv5z/I7JHdaNusidUlWcpv2NJaX1Dbz5RS+5RSzcpatZoB+2u420BgqFJqIpAExCqlCrXWU2u4b9gYcRmefYeO8MuF6xk8dgbxiUlhqrR2cjYlhLATCR2iLjFxcZwzfgb3zZ9OuxQvSin6dsjgikGdrC7NdKF2I74NjAJml/3/VvU7aK0rLvqnlMoB+podtCD0GYm5Bw5z1+INDBk3k7iExDBWWjvZsYlgSJebMeT3GH7yO448nphYzr19Fr6ybu1Va94k791/M/bi6Fp9PtSwNRt4TSk1BtgJXAOglOoL3K61Hhvi8xsi2BmJm3fu59CRY5woKua5j3PJHj+L2Lh4s8oWwhDS5WYM+T2GXzT9jqMpWCqlcHtK40b3869m4+o3eXbF10wY3tviyswTUtjSWh+khkHvWusvgdOCltZ6IbAwlNcMRjAzEpes/J4P9iaR2qYbyuVi2LiJxMTFmVm2EELUS11DDaLp4O4E0RQsq+t6zhX8+EkMT739JZMvM3WBAstExQry9b0Mz8L3v2NDcRaDRl5nVonCoeQAVrtw/m4CGb9o9OsXHNhbZTmFciVH8+r9XOFS1/ualjMiag/uwn66DBnOps89zHnjM+66sp/V5YRdVIQtf5fhOVVcwi//soYT8ekApHfoyZnn/tyM0gwnB39zRfPZqT/h/N0E8rds9Otr5aJ5zhOn3f6/ubcE9XzRIND9UeX1wfbs2FJxu9vtPm1mpYgcnQdczPavE8lZ8Ako4Og+5o7LJikx8nqRoiJs1aXoVDF3zFtNhyvupkmzVlaXEzKnHPwlFAoR+QLdH5Xf79u5E4hLa11xe1HezrDXKKzVrvdQ2vUeCsDRgoPc/twjPD1+KA2TEiyuzFhRGba+276PZ97fRGxsLIeOnqT71b+hcdPmVpcVVQLdCUsoC50sGWIMl3LVePB3KbkGnFHc8YnkLpxS8X1x4SGK0prK32qUSE5tQt+ch5nw/EM8PXYIjVKsmfkfDlEXtr7ekssfV/5Eds7vcLndVpcj/HBKS51dSDgNn4ZN0miR1fG024uapFlQTWSqfkmh7fMnh2UxVjuI9JOgYPdFDVJSOXv0DCYueIi5tw4MaD3MvIJCbpu9mOd/e7Oh1zw2UlSFrXU/7uapT/LIHn1/va9ILgcxYx0+mFdlbEbl263m5G0t4VTUJtIP7nZQn32H3fcloQplX5SYnMLAWx/hjgUP0b9t6d/n2Z2aMbhbzUN9Fq1YS/7eXYZd8zgcoiZsrf1hF89+VkB2zn34u2xQTeQgZiyf9lUZm1H5dqvVZ1vLAax2Vv9ujH59q99PqCL94G4HcpwwTkKDZIZN/D0nCo8A8OKHSzl0dAuXDqjaumzE1WHMELFhS2vNtj15eL0+Nu3J5+9bYOgt9wYVtJzE6QcEp5EDWO2s/t0Y/fpWvx8nCnR/JPst+6ncSldwYC+6bGyiS7loWNZ1Hu7Wfo8nhuTU0msqnv2L21n+9gIK3v+W/p0yUErRoWVayFeHMUtEhi2tNdOXfEpugzOIb5BKbGJrBt1wfsQHLXDOAUFpX5WBsJVvF0JEhkD3R07Zb0WTyq10386dULHsSVHezoqxi2a32PW9bAzfffUxX2w6QMmpIkreeJet329g6bUpQOBXh7FCxIUtrTX3vfQx7t5X079b5C+U5lSp6ZkBNbfLGa8wm5PH7AkR6Tr2GVrx9RvPbMV36gSpCY2AwK4OYxXbhq36zC7Yn3+UXy9aR2xKE7xeL60GXEurM/qYVKkIJzm41Y+E09DJuBshQmfGvmj/jk0cOplA81k7adU4vqL3qrarw1jJtmEr0NkFP+Ud5ld/3cDgMTOJTwxfs6EcxIxl59+nnWvzR8KpENZx8r7DaGbsi277w2IADuzZwfa3/8TTt51LXGxM2F83GLYNW3XNLnjrsy2s/nE/SsG+4zBk3Ezi4uu32mx9uwrkIGYsO/8+7VybEOH06KTr2f3fLRWDocu5lIsWbdrKZ8MP+f1YI71FFu4r7+HWpx8nIzWBkpISbrvwDLplZRj+WsGu6WXbsFXb7IJX1vzAR4cz6H1L6eDqLkE+v3QVCCGMFAljvQoLj+JJTjvtGpBFeTsp/OBJi6oSVqjcSldyNK/iGqAu5apYyNdOLXaNM1tyzuQ/AeDzepn1wgzuvchHz/bNDH2dYNf0sm3YuqVPg4r/y2cXrPjyv3xxshW9f36DxdWJSBAJB8dI56RtJCdwIpLY7fNVHy63m2FjHuQPL87iV15N307GXI4vlDW9bBu20pI8Ff+P6OBi4pzXaTrwanpefI3fxzppBy2sIwdH+7NiG8m4GyGcz+VykT16Gn9e9Hvu8PoY0KVlyM8Zyppetg1bZ83dR4lPA1BwrISY1ALufcB/0AI5iDqJBGNhN/J3J0RkcLlcDB01lWcXP0bhiSJ6tm2KUoq01KR6P1d5q9ZrI0tPuuq7ppdtw9aZ/QYT06IHSimaZJ1B256DrS5JhIEEYyGEEOGilGLwTffw1qo3WfrfQxSdPE4W3/DQDYPrtdB5eatW9V63QFu3bBu2ulwzlUZNjR3YVpl0FQgjOa2Fzmn1CnMkJSVTcGBLxWDocuWzEYVwIqUUZ553ZcX3//vucx7465vMuHkISin6T3iavKNFpz0uLTmOL569A4DVX20md38RL3+3v8p9Al3Ty7ZhK5xBC6SrQBjLaS10TqvXCSLhBE72iyIatOkxgJ1uD1MXvsbsnGzyjhbRbdzjp91v41/urvj67ccnhfSatg1bQoRbJBwcI52TtpEEFSGco3XXvux2x/DrBX9Fax3Sc5WvvfX3j+9sorU+WNN9IjJsGb2Dli6XyOTkbRctf5OR9F5E9IiWz6fTtezckz1uNwde/5AfP1wK2kdWvwtIaNikXs9TvvZWwzjGA4/WdJ+IDFtG/zFLl0v4OKnlIlB7d23H6/UCkJ+3n2k5IwBjd7R2/puUA42Idnb+fIqqWnToTmKTFqSdNxZfcRGb3n2OzkN/TkJq04AeX3ntrYufKxxFNIUt4RyRePD1er3EpbUGICapccVON1p2tHKgEUI4kSsmjmYXT2DTe/PoNPhnAT2m8tpbN50ZU2umkrAlhAEqt9Dl5+0nJqkxAO74RCvLqlUktigKIUQwqu8Ptdasm7eGds0a1fm46mtv3dEvtrC2+0rYEsIAlVvopuWMqLFlx04isUVRCCGCUdP+sKSkmI/mP8zGHfvo3LL0WpAej7vKfaqvvdUs2VVS22tI2BJCCCGEqMTjiWHY2Ok88Y8XKV6zhZMnjpHdUjFxRJ+K+1Rfe2v3vqNpe6fX/Hwq1CmP0cAdn7Qed0z6aT/wFh/wnizsF8xzKqXGa62fD7k4YYm6tp+7QaMdrSYvzqt++66nbkrzHsvPMuL1w/E3aRQz3n8o5LPnbE7Yfnb+fFrNCdsvHCRsWUQp9aXWuq/VdYjgyPZzLtl2zibbz9midfu5rC5ACCGEECKSSdgSQgghhAgjCVvWibo+6wgj28+5ZNs5m2w/Z4vK7SdjtoQQQgghwkhatoQQQgghwkjClkmUUo2VUu8rpbaU/V/r0rRKqRSl1B6l1FwzaxS1C2T7KaV6KaU+U0ptVEp9q5S61opaRSml1M+UUpuUUluVUlNr+HmcUurVsp+vU0plmV+lqE0A2+8updQPZZ+1D5VSbayoU5zO37ardL+rlVJaKRXxsxMlbJlnKvCh1roj8GHZ97WZAawxpSoRqEC233HgFq11N+BnwBNKqVQTaxRllFJu4GngEqArcL1Sqmu1u40B8rXWHYA/Ab83t0pRmwC339dAX631mcAy4A/mVilqEuC2QymVDNwJrDO3QmtI2DLP5cBLZV+/BFxR052UUmcBGcB7JtUlAuN3+2mtN2utt5R9nQvsB05f2FCYoT+wVWu9XWt9CniF0m1YWeVtugw4XymlTKxR1M7v9tNar9JaHy/79nOgpck1ipoF8tmD0kaFPwAnzSzOKhK2zJOhtf4JoOz/ptXvoJRyAY8D95hcm/DP7/arTCnVH4gFtplQmzhdC2BXpe93l91W43201iXAYaCJKdUJfwLZfpWNAf4V1opEoPxuO6VUb6CV1nq5mYVZSa6NaCCl1AdAZg0/mhbgU0wE/qm13iUn2OYzYPuVP08z4K/AKK21z4jaRL3V9AGqPvU6kPsIawS8bZRSNwF9gWFhrUgEqs5tV9ao8Ccgx6yC7EDCloG01hfU9jOl1D6lVDOt9U9lB+P9NdxtIDBUKTURSAJilVKFWuu6xncJgxiw/VBKpQArgPu11p+HqVTh326gVaXvWwK5tdxnt1LKAzQEDplTnvAjkO2HUuoCSk+Ghmmti0yqTdTN37ZLBroDq8saFTKBt5VSl2mtvzStSpNJN6J53gZGlX09Cnir+h201jdqrVtrrbOAXwOLJGjZht/tp5SKBd6gdLstNbE2cbr1QEelVNuy7XIdpduwssrb9GpgpZaFB+3C7/Yr64qaB1ymta7x5EdYos5tp7U+rLVO01pnlR3rPqd0G0Zs0AIJW2aaDVyolNoCXFj2PUqpvkqp+ZZWJgIRyPYbCWQDOUqpb8r+9bKm3OhWNgZrEvAu8CPwmtZ6o1LqEaXUZWV3WwA0UUptBe6i7hnCwkQBbr/HKO0BWFr2WasepoUFAtx2UUdWkBdCCCGECCNp2RJCCCGECCMJW0IIIYQQYSRhSwghhBAijCRsCSGEEEKEkYQtIYQQQogwkrAlhBBCCBFGEraEEEIIIcJIwpYQQgghRBj9Hwnu73TNYMauAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,6))\n",
    "plot_decision_regions(np.array(data.drop('y',axis=1)), np.array(data['y']), clf=best_model, legend=2)\n",
    "plt.xlim(-0.5,0.5)\n",
    "plt.ylim(-0.5,0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This looks classy :D"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (i) Comment on your results."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that logistic regression with 2 features, and svc both performed very poorly. We got good results when we tried logiswtic regression while adding more features, but we got the best result from using svm with non linear kernel"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. At the end of Section 9.6.1, it is claimed that in the case of data that is just barely linearly separable, a support vector classifier with a small value of cost that misclassifies a couple of training observations may perform better on test data than one with a huge value of cost that does not misclassify any training observations. You will now investigate this claim.\n",
    "\n",
    "\n",
    "\n",
    " \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (a) Generate two-class data with p = 2 in such a way that the classes are just barely linearly separable.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "#set seed \n",
    "np.random.seed(1)\n",
    "X = np.random.normal(size = (200,2))\n",
    "y = 1*(X[:,0] + X[:,1] > 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>X1</th>\n",
       "      <th>X2</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.624345</td>\n",
       "      <td>-0.611756</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.528172</td>\n",
       "      <td>-1.072969</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.865408</td>\n",
       "      <td>-2.301539</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.744812</td>\n",
       "      <td>-0.761207</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.319039</td>\n",
       "      <td>-0.249370</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         X1        X2  y\n",
       "0  1.624345 -0.611756  1\n",
       "1 -0.528172 -1.072969  0\n",
       "2  0.865408 -2.301539  0\n",
       "3  1.744812 -0.761207  1\n",
       "4  0.319039 -0.249370  1"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#making a dataframe\n",
    "df = pd.DataFrame({'X1':X[:,0],'X2':X[:,1],'y':y})\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x27e746a3da0>"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x = 'X1',y = 'X2',hue = 'y',data = df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(100, 2) (100, 2)\n"
     ]
    }
   ],
   "source": [
    "#dividing it into train and test \n",
    "X_train,X_test,y_train,y_test = train_test_split(df.drop('y',axis=1),df['y'],test_size = 0.5,random_state = 1)\n",
    "print(X_train.shape,X_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (b) Compute the cross-validation error rates for support vector classifiers with a range of cost values. How many training errors are misclassified for each value of cost considered, and how does this relate to the cross-validation errors obtained?\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [],
   "source": [
    "training_scores_dict = {}\n",
    "cross_val_scores_dict = {}\n",
    "cost_values = np.logspace(-2,6,20)\n",
    "\n",
    "for cost in cost_values:\n",
    "    svc = SVC(kernel = 'linear',C = cost)\n",
    "    svc.fit(X_train,y_train)\n",
    "    training_scores_dict[cost] = svc.score(X_train,y_train)\n",
    "    cross_val_scores_dict[cost] = np.mean(cross_val_score(svc,X_train,y_train,cv = 10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Accuracy')"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,6))\n",
    "plt.plot(list(training_scores_dict.keys()),list(training_scores_dict.values()),marker = 'o',label = 'Training scores')\n",
    "plt.plot(list(cross_val_scores_dict.keys()),list(cross_val_scores_dict.values()),marker = 'o',label = 'CV Scores')\n",
    "# plt.plot(min(training_scores_dict, key=training_scores_dict.get),min(list(training_scores_dict.values())),marker = 'o',markersize = 8,c='r',label = 'min_error')\n",
    "plt.legend()\n",
    "plt.xscale('log')\n",
    "plt.xlabel('Cost(log)')\n",
    "plt.ylabel('Accuracy')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (c) Generate an appropriate test data set, and compute the test errors corresponding to each of the values of cost considered. Which value of cost leads to the fewest test errors, and how does this compare to the values of cost that yield the fewest training errors and the fewest cross-validation errors?\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_scores_dict = {}\n",
    "cost_values = np.logspace(-2,6,20)\n",
    "\n",
    "for cost in cost_values:\n",
    "    svc = SVC(kernel = 'linear',C = cost)\n",
    "    svc.fit(X_train,y_train)\n",
    "    test_scores_dict[cost] = svc.score(X_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Accuracy')"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,6))\n",
    "plt.plot(list(training_scores_dict.keys()),list(training_scores_dict.values()),marker = 'o',label = 'Training scores')\n",
    "plt.plot(list(cross_val_scores_dict.keys()),list(cross_val_scores_dict.values()),marker = 'o',label = 'CV Scores')\n",
    "plt.plot(list(test_scores_dict.keys()),list(test_scores_dict.values()),marker = 'o',label = 'Test Scores')\n",
    "\n",
    "plt.plot(max(test_scores_dict, key=test_scores_dict.get),max(list(test_scores_dict.values())),marker = 'o',markersize = 8,c='r',label = 'best_accuracy')\n",
    "plt.legend()\n",
    "plt.xscale('log')\n",
    "plt.xlabel('Cost(log)')\n",
    "plt.ylabel('Accuracy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The best test accuracy is when cost  =  0.4832930238571752\n"
     ]
    }
   ],
   "source": [
    "print('The best test accuracy is when cost  = ',max(test_scores_dict, key=test_scores_dict.get))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (d) Discuss your results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The training accuracy always increasess with increase in the value of C, so, we cant' use that to decide which is the best value of C for this data, so, we will analyze the test error, we can see that the test error is the highest at a point and then becomes steady, so we will use that value of C for our final model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7. In this problem, you will use support vector approaches in order to predict whether a given car gets high or low gas mileage based on the Auto data set.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(397, 9)\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mpg</th>\n",
       "      <th>cylinders</th>\n",
       "      <th>displacement</th>\n",
       "      <th>horsepower</th>\n",
       "      <th>weight</th>\n",
       "      <th>acceleration</th>\n",
       "      <th>year</th>\n",
       "      <th>origin</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>18.0</td>\n",
       "      <td>8</td>\n",
       "      <td>307.0</td>\n",
       "      <td>130</td>\n",
       "      <td>3504</td>\n",
       "      <td>12.0</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "      <td>chevrolet chevelle malibu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15.0</td>\n",
       "      <td>8</td>\n",
       "      <td>350.0</td>\n",
       "      <td>165</td>\n",
       "      <td>3693</td>\n",
       "      <td>11.5</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "      <td>buick skylark 320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>18.0</td>\n",
       "      <td>8</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150</td>\n",
       "      <td>3436</td>\n",
       "      <td>11.0</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "      <td>plymouth satellite</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16.0</td>\n",
       "      <td>8</td>\n",
       "      <td>304.0</td>\n",
       "      <td>150</td>\n",
       "      <td>3433</td>\n",
       "      <td>12.0</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "      <td>amc rebel sst</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17.0</td>\n",
       "      <td>8</td>\n",
       "      <td>302.0</td>\n",
       "      <td>140</td>\n",
       "      <td>3449</td>\n",
       "      <td>10.5</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "      <td>ford torino</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    mpg  cylinders  displacement horsepower  weight  acceleration  year  \\\n",
       "0  18.0          8         307.0        130    3504          12.0    70   \n",
       "1  15.0          8         350.0        165    3693          11.5    70   \n",
       "2  18.0          8         318.0        150    3436          11.0    70   \n",
       "3  16.0          8         304.0        150    3433          12.0    70   \n",
       "4  17.0          8         302.0        140    3449          10.5    70   \n",
       "\n",
       "   origin                       name  \n",
       "0       1  chevrolet chevelle malibu  \n",
       "1       1          buick skylark 320  \n",
       "2       1         plymouth satellite  \n",
       "3       1              amc rebel sst  \n",
       "4       1                ford torino  "
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(r'E:\\programming\\dataset\\Into_to_statstical_learning\\Auto.csv')\n",
    "print(data.shape)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you have done the previous notebooks too, you must know there's something wrong with this data....remember...\n",
    "think.....\n",
    "HORSEPOWER...has some '?'. \n",
    "SO, lets remove if first "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['horsepower'] = data['horsepower'].replace('?',np.nan)\n",
    "data.dropna(inplace = True)\n",
    "data['horsepower'] = data['horsepower'].astype('int')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (a) Create a binary variable that takes on a 1 for cars with gas mileage above the median, and a 0 for cars with gas mileage below the median.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['mpg_binary'] = np.where(data['mpg'] > np.median(data['mpg']),1,0)\n",
    "X = data.drop(['mpg','name','mpg_binary'],axis=1)\n",
    "y = data['mpg_binary']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (b) Fit a support vector classifier to the data with various values of cost, in order to predict whether a car gets high or low gas mileage. Report the cross-validation errors associated with different values of this parameter. Comment on your results.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 95%|█████████████████████████████████████████████████████████████████████████████▉    | 19/20 [10:49<00:42, 42.03s/it]"
     ]
    }
   ],
   "source": [
    "from tqdm import tqdm\n",
    "svc_scores_dict = {}\n",
    "cost_values = np.logspace(-2,6,10)\n",
    "\n",
    "for cost in tqdm(cost_values):\n",
    "    svc = SVC(kernel = 'linear',C = cost)\n",
    "    svc.fit(X,y)\n",
    "    svc_scores_dict[cost] = np.mean(cross_val_score(svc,X,y,cv=10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize = (10,6))\n",
    "plt.plot(list(svc_scores_dict.keys()),list(svc_scores_dict.values()),marker = 'o')\n",
    "plt.plot(max(svc_scores_dict, key=svc_scores_dict.get),max(list(svc_scores_dict.values())),marker = 'o',markersize = 8,c='r',label = 'max_accuracy')\n",
    "plt.legend()\n",
    "plt.xscale('log')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (c) Now repeat (b), this time using SVMs with radial and polynomial basis kernels, with different values of gamma and degree and cost. Comment on your results.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm import tqdm\n",
    "rbf_scores_dict = {}\n",
    "poly_scores_dict = {}\n",
    "\n",
    "cost_values = np.logspace(-2,6,20)\n",
    "\n",
    "for cost in tqdm(cost_values):\n",
    "    rbf = SVC(kernel = 'rbf',C = cost)\n",
    "    rbf.fit(X,y)\n",
    "    rbf_scores_dict[cost] = np.mean(cross_val_score(rbf,X,y,cv=10))\n",
    "    \n",
    "    poly = SVC(kernel = 'poly',C = cost)\n",
    "    poly.fit(X,y)\n",
    "    poly_scores_dict[cost] = np.mean(cross_val_score(poly,X,y,cv=10))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize = (10,6))\n",
    "plt.plot(list(rbf_scores_dict.keys()),list(rbf_scores_dict.values()),marker = 'o')\n",
    "plt.plot(list(poly_scores_dict.keys()),list(poly_scores_dict.values()),marker = 'o')\n",
    "plt.legend()\n",
    "plt.xscale('log')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Last question in a separate notebook....."
   ]
  }
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